AI Software Engineer Jobs

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Company OverviewDeepgram is the leading voice AI platform for developers building speech-to-text (STT), text-to-speech (TTS) and full speech-to-speech (STS) offerings. 200,000+ developers build with Deepgram’s voice-native foundational models – accessed through APIs or as self-managed software – due to our unmatched accuracy, latency and pricing. Customers include software companies building voice products, co-sell partners working with large enterprises, and enterprises solving internal voice AI use cases. The company ended 2024 cash-flow positive with 400+ enterprise customers, 3.3x annual usage growth across the past 4 years, over 50,000 years of audio processed and over 1 trillion words transcribed. There is no organization in the world that understands voice better than DeepgramNote: this role is based out of the EMEA territory.The OpportunityDeepgram is expanding globally and building a true follow‑the‑sun model. We are hiring a Solutions Architect in EMEA to own complex post‑sales engagements, guide customers to production, and strengthen our technical support coverage for the region. You will work across the full customer lifecycle, with a primary focus on architecture, implementation, and Tier‑3 technical problem solving. You will also contribute to pre‑sales validation when deep technical credibility is needed, partner with Product and Engineering on feedback and roadmap, and help mature our global operations.About Applied Engineering at DeepgramApplied Engineering combines functions that other companies split across Solutions Engineering, Solutions Architecture, Consulting, and Senior Technical Support. We are the technical interface from first discovery through successful production and beyond. The team partners closely with Sales, Customer Success, Product, and DevRel to deliver an enterprise‑grade experience that is fast, clear, and outcome‑oriented.What You’ll DoLead architecture and implementation for enterprise deployments that use Deepgram’s speech‑to‑text, text‑to‑speech, and voice‑agent capabilities.Own post‑sales technical success for assigned accounts. Unblock integrations, optimize accuracy and latency, and guide customers to stable production.Serve as the Tier‑3 escalation point for complex issues. Drive root cause analysis, propose mitigations, and write durable fixes or automation when possible.Design reference architectures and implementation patterns for common EMEA customer use cases including contact centers, voice analytics, QA, and AI agents.Build high‑quality samples, internal tools, or scripts that make repeatable tasks easier for customers and for our team.Contribute to pre‑sales discovery and POCs when deep technical direction is needed. Translate business goals to a concrete plan with clear success criteria.Partner with Product and Engineering to prioritize fixes and features. Bring crisp customer signals that improve our roadmap.Contribute to knowledge systems. Capture runbooks, playbooks, and docs that scale your expertise across regions.Participate in an on‑call or incident rotation appropriate for the region and customer support tier. Help us meet or outperform regional SLAs.Regional ExpectationsBased in an EMEA time zone with reliable overlap to customer business hours.Excellent written and spoken English. Additional European languages are a strong plus.Familiarity with GDPR, data privacy expectations, and enterprise security reviews common across EMEA.Ability to travel within the region for critical customer milestones, estimated 10–20 percent.Your First 90 DaysFirst 30 daysRamp on Deepgram’s platform, APIs, SDKs, self-hosted deployments, and support practices. Shadow calls across pre-sales, post-sales, and support. Begin owning low-risk technical tasks for an active account and contribute improvements to runbooks or sample code.By day 60Own two to three customer workstreams end-to-end. Lead discovery for one new implementation or migration. Publish one reusable asset such as a deployment guide, Helm example, or troubleshooting playbook.By day 90Act as primary technical owner for several EMEA accounts in production. Close at least one complex investigation with measurable customer impact. Present a short readout on a repeated regional pattern and the automation or content you created to solve it.You’ll Thrive Here If YouEnjoy solving hard customer problems at the code, container, and cloud layers.Like translating messy real‑world constraints into clear architectures and plans.Are comfortable writing and reading production‑grade code, not just sample snippets.Value crisp documentation, reproducible runbooks, and operational excellence.Care about delivering outcomes, not just closing tickets.Minimum Qualifications5 or more years in Solutions Architecture, Solutions Engineering, or similar customer‑facing technical roles.Professional software engineering experience in at least one language such as Python, Rust, or JavaScript. You can build POCs and tools that real users run.Hands‑on experience with modern cloud platforms. Comfortable with containerization and orchestration, for example Docker and Kubernetes, and with secure network design for API‑driven systems.Proven ownership of complex post‑sales work such as production deployments, migrations, performance tuning, and incident response.Clear written and verbal communication across both technical and executive audiences.Preferred QualificationsExperience with speech recognition, TTS, or building voice agents that orchestrate LLMs.Familiarity with WER analysis, model selection and tuning, and accuracy‑versus‑latency tradeoffs.Experience operating self‑hosted systems, including Helm‑based deployments and observability for production services.Strong understanding of authentication, authorization, data residency, and compliance topics that appear in EMEA enterprise reviews.Fluency in an additional European language such as German, French, Dutch, Italian, or Spanish.How We WorkRemote across EMEA with periodic regional meetups.Collaboration with colleagues in the Americas and APAC to support continuous coverage.Shared playbooks, defined escalation paths, and measurable SLAs.Interview ProcessRecruiter screen focused on experience, motivations, and logistics.Hiring manager conversation focused on technical depth and customer impact.Technical assessment that mirrors real work. Expect practical coding, architecture discussion, and debugging.Panel interviews with cross‑functional partners.A presentation simulating a post-sales customer engagement, based on a provided case study. Additionally, you’ll be asked to present a past customer‑facing technical engagement that you led, including the problem, your approach, and measurable outcomes.If this sounds like you, we would love to meet you!Backed by prominent investors including Y Combinator, Madrona, Tiger Global, Wing VC and NVIDIA, Deepgram has raised over $85 million in total funding. If you're looking to work on cutting-edge technology and make a significant impact in the AI industry, we'd love to hear from you!Deepgram is an equal opportunity employer. We want all voices and perspectives represented in our workforce. We are a curious bunch focused on collaboration and doing the right thing. We put our customers first, grow together and move quickly. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, pregnancy, parental status, genetic information, political affiliation, or any other status protected by the laws or regulations in the locations where we operate.We are happy to provide accommodations for applicants who need them.

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Company OverviewDeepgram is the leading voice AI platform for developers building speech-to-text (STT), text-to-speech (TTS) and full speech-to-speech (STS) offerings. 200,000+ developers build with Deepgram’s voice-native foundational models – accessed through APIs or as self-managed software – due to our unmatched accuracy, latency and pricing. Customers include software companies building voice products, co-sell partners working with large enterprises, and enterprises solving internal voice AI use cases. The company ended 2024 cash-flow positive with 400+ enterprise customers, 3.3x annual usage growth across the past 4 years, over 50,000 years of audio processed and over 1 trillion words transcribed. There is no organization in the world that understands voice better than DeepgramNote: this role is based out of the EMEA territory.OpportunityDeepgram is expanding globally and operating a follow-the-sun model. We are hiring a Pre-sales Solutions Engineer in EMEA to win complex technical evaluations, design clear solution paths, and drive repeatable adoption for strategic accounts. Our strategic Account Executives do not hand off their customers after the first sale, so you will partner long-term across discovery, POC, production launch, and expansion. You will focus on pre-sales, yet you will often step into post-sales style work when the stakes are high and continuity matters.About Applied Engineering at Deepgram Applied Engineering blends what many companies split into Solutions Engineering, Solutions Architecture, Solutions Consulting, and Technical Support. We are builders and communicators who bridge sales and engineering. We help customers move from problem to production with speed, clarity, and measurable outcomes.What You’ll DoLead technical discovery for strategic opportunities. Map business goals to measurable technical success criteria and an evaluation plan.Design, scope, and execute POCs that prove value. Define datasets, metrics, and timelines that land a clear technical win.Build lightweight prototypes, sample integrations, and demos using Deepgram SDKs and APIs. Show, do not tell.Advise on architecture for accuracy, latency, scalability, and cost. Cover cloud, self-hosted, hybrid, and data residency needs.Run security and compliance threads common in EMEA. Prepare crisp responses for GDPR, ISO 27001, SOC 2, and vendor risk reviews.Triage and debug issues during evaluations. Collaborate with Product, Engineering, and Support to unblock customers quickly.Create reusable assets that scale. Turn repeated requests into working samples, reference architectures, runbooks, and field guides.Partner with Solutions Architects and Support for seamless continuity after initial wins. Stay involved through expansion phases when needed.Enable the field. Collaborate with AEs, CSMs, and partners on positioning, demos, and technical validation for priority use cases.Regional ExpectationsBased in an EMEA time zone with strong overlap to customer business hours.Excellent written and spoken English. Additional European languages are a strong plus.Familiarity with procurement, InfoSec, and data privacy expectations across EMEA, including GDPR and data residency.Your First 90 DaysIn the first weeks you will pick up low-risk customer tickets to learn our systems and support flow, then progress to pre-sales escalations tied to active opportunities and engagements driven by Account Executives or partners.First 30 daysRamp on Deepgram’s product surface area, platform APIs, SDKs, evaluation methodology, and security review materials.Shadow strategic discovery and POC calls.Triage and resolve low-risk tickets with a Solutions Architect or Support partner. Focus on reproductions, log and trace collection, SDK setup issues, and clear notes and handoffs.Publish one internal field guide that clarifies a common EMEA pre-sales topic (for example data residency, telephony capture, or evaluation metrics).By day 60Own two evaluations end to end with defined success criteria and timelines.Serve as the named technical partner for one or two strategic AEs. Run weekly technical deal reviews and prepare objection handling packs.Take point on higher signal tickets related to your evaluations, coordinating fast fixes with Product, Engineering, and Support.Deliver one live demo that becomes a reusable asset for the region. Pair with a Solutions Architect on a production launch to learn handoffs and escalation paths.By day 90Act as the primary pre-sales technical owner for several opportunities and expansions within strategic accounts.Close at least one complex technical win with a measurable impact on revenue.Lead one customer architecture workshop that documents a reference plan for production rollout or expansion.Convert repeated ticket patterns into a runbook, sample, or accelerator and present a short readout on the impact.You Will Thrive Here If YouEnjoy the mix of customer conversations and hands-on building.Can move from whiteboard to working code and back without losing the thread.Communicate clearly with executives and deeply with engineers.Value speed with rigor and crisp documentation.Like winning together across regions and functions.Minimum Qualifications5 or more years in Solutions Engineering or a similar customer-facing technical role focused on pre-sales.Professional software engineering experience in at least one language such as JavaScript/TypeScript, Python, or Rust. You can build POCs and tools that real users run.Hands-on experience with modern cloud platforms. Comfortable with Docker, Kubernetes, networking fundamentals, and secure API design.Proven track record leading POCs for enterprise customers and earning the technical win.Clear written and verbal communication across both technical and executive audiences.Preferred QualificationsExperience with speech recognition, TTS, voice quality analysis, or AI agents that orchestrate LLMs.Familiarity with telephony and real-time media concepts such as SIP, WebRTC, streaming, and WebSocket integrations.Experience with self-hosted and hybrid deployments, including Helm-based installs and production observability.Strong understanding of authentication, authorization, and data residency topics that appear in EMEA enterprise reviews.Fluency in an additional European language such as German, French, Dutch, Italian, or Spanish.How We WorkRemote across EMEA with periodic regional meetups.Close partnership with AEs, SAs, Product, and Engineering to support continuous coverage across EMEA, the Americas, and APAC.Shared playbooks, defined escalation paths, and measurable SLAs.Interview ProcessRecruiter screen focused on experience, motivations, and logistics.Hiring manager conversation focused on technical depth and customer impact.Practical assessment that mirrors real work. Expect discovery, solution design, and a short hands-on exercise.Panel interviews with cross-functional partners.Simulated pre-sales engagement based on a case study, along with and architecture walkthrough of a past technical win. Show your approach to success criteria, trade offs, and outcomes.Backed by prominent investors including Y Combinator, Madrona, Tiger Global, Wing VC and NVIDIA, Deepgram has raised over $85 million in total funding. If you're looking to work on cutting-edge technology and make a significant impact in the AI industry, we'd love to hear from you!Deepgram is an equal opportunity employer. We want all voices and perspectives represented in our workforce. We are a curious bunch focused on collaboration and doing the right thing. We put our customers first, grow together and move quickly. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, pregnancy, parental status, genetic information, political affiliation, or any other status protected by the laws or regulations in the locations where we operate.We are happy to provide accommodations for applicants who need them.

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Perplexity is an AI-powered answer engine founded in December 2022 and growing rapidly as one of the world’s leading AI platforms. Perplexity has raised over $1B in venture investment from some of the world’s most visionary and successful leaders, including Elad Gil, Daniel Gross, Jeff Bezos, Accel, IVP, NEA, NVIDIA, Samsung, and many more. Our objective is to build accurate, trustworthy AI that powers decision-making for people and assistive AI wherever decisions are being made. Throughout human history, change and innovation have always been driven by curious people. Today, curious people use Perplexity to answer more than 780 million queries every month–a number that’s growing rapidly for one simple reason: everyone can be curious. Introduction At Perplexity AI, the Sonar API powers AI-native search, retrieval, and automation for some of the world’s most innovative companies. Our Support team is the frontline for developer and enterprise success—ensuring that customers can build fast, reliable, and differentiated products on top of Sonar’s capabilities. We don’t just answer tickets—we partner deeply with customers, Product, and Engineering to architect solutions, debug complex integrations, and influence the roadmap based on real-world developer needs. About the Role We’re looking for a Customer Success Engineer to be a hands-on technical partner for our Sonar API customers. This is a deeply technical, customer-facing role—equal parts solution architect, developer advocate, and technical program manager. You’ll work end-to-end with developers, product teams, and executives at our customers’ organizations—from designing their Sonar-powered architecture to optimizing query performance and implementing new features. You’ll also contribute to internal tooling, docs, and demos that make Sonar adoption easier and more impactful. This role is ideal for TPMs, solutions engineers, or software engineers who have moved into customer-facing work but still want to build, prototype, and problem-solve daily. Key Responsibilities Serve as the dedicated technical partner for strategic Sonar API customers, guiding them through architecture design, integration, and optimization. Troubleshoot API performance, grounding quality, and integration challenges—diving directly into code and logs when needed. Prototype example integrations, search workflows, and demos to accelerate adoption and inspire customer innovation. Collaborate with Engineering and Product to resolve high-priority escalations, ensuring minimal downtime and maximum reliability. Capture and synthesize customer feedback to improve Sonar’s API features, SDKs, and developer experience. Maintain deep familiarity with Sonar’s latest capabilities, competitive positioning, and best practices, and use this knowledge to advise customers. What We’re Looking For Must-Haves 5+ years in technical support engineering, software engineering, or solutions engineering, with direct application development experience. Strong API integration skills—able to design and debug REST/JSON payloads, manage auth flows, and optimize latency. Proven track record of diagnosing complex technical issues across distributed systems, APIs, and customer environments. Excellent communicator who can work with both developer teams and non-technical stakeholders. Bachelor’s degree in Computer Science or equivalent hands-on experience. Nice-to-Haves Experience working with search, retrieval-augmented generation (RAG), or AI/ML APIs. Background in developer tools or platform engineering, especially in high-scale or low-latency environments. Strong familiarity with Python or JavaScript for building integrations, SDKs, or prototypes. History of working at startups or small teams where you owned customer projects end-to-end. Why Join Us The Sonar API is quickly becoming a core infrastructure layer for AI-powered search and automation. As a Customer Success Engineer, you’ll help shape how our customers—from startups to Fortune 500s—bring their most ambitious ideas to life. You’ll be joining a fast-moving, high-impact team where your technical skills, creativity, and ability to bridge product and customer needs will directly influence both Sonar’s roadmap and its market success. Final offer amounts are determined by multiple factors, including, experience and expertise, and may vary from the amounts listed above.   Equity: In addition to the base salary, equity may be part of the total compensation package. Benefits: Comprehensive health, dental, and vision insurance for you and your dependents. Includes a 401(k) plan.  

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Shape the Future of AI At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially. About Labelbox We're the only company offering three integrated solutions for frontier AI development: Enterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling Why Join Us High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions. Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence. Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution. Continuous Growth: Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI. Clear Ownership: You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics. Role Overview As an Applied Research Engineer at Labelbox, you’ll sit at the junction of advanced AI research and real product impact, with a focus on the data that makes modern agents work—browser interactions, SWE/code traces, GUI sessions, and multi-turn workflows. You’ll drive the data landscape required to advance capable, adaptable agents and help shape Labelbox’s strategy for collecting, synthesizing, and evaluating it. You will possess expertise in LLM agents and planning/execution loops, plus creativity in tackling problems across data design, interaction, and measurement. You’ll publish meaningful results, collaborate with customer researchers in frontier AI labs, and turn prototypes into reliable, scalable features. Your Impact Create frameworks and tools to construct, train, benchmark and evaluate autonomous agent capabilities. Design agent-focused data programs using supervised fine-tuning (SFT) and reinforcement learning (RL) methodologies. Develop data pipelines from diverse sources like code repositories, web browsers, and computer systems. Implement and adapt popular open-source agent libraries and benchmarks with proprietary datasets and models. Engage with research teams in frontier AI labs and the wider AI community to understand evolving agent data needs for frontier models and share best practices. Collaborate closely with frontier AI lab customers to understand requirements and guide model development. Publish research findings in academic journals, conferences, and blog posts. What You Bring Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or related field. At least 3 years of experience addressing sophisticated ML problems with successful delivery to customers. Experience building and training autonomous agents—tool use, structured outputs, multi-step planning—across browsers/GUI, codebases, and databases using SFT and RL. Constructed and evaluated agentic benchmarks (e.g. SWE-bench, WebArena, τ-bench, OSWorld) and reliability/efficiency suites (e.g. WABER).  Adept at interpreting research literature and quickly turning new ideas into prototypes. Deep understanding of frontier models (autoregressive, diffusion), post-training (SFT, RLVR, RLAIF, RLHF, et al.), and their human data requirements. Proficient in Python, data science libraries and deep learning frameworks (e.g., PyTorch, JAX, TensorFlow). Strong analytical and problem-solving abilities in ambiguous situations. Excellent communication skills. Track record of publications in top-tier AI/ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, etc.). Labelbox Applied Research At Labelbox Applied Research, we're committed to pushing the boundaries of AI and data-centric machine learning, with a particular focus on advanced human-AI interaction techniques. We believe that high-quality human data and sophisticated human feedback integration methods are key to unlocking the next generation of AI capabilities. Our research team works at the intersection of machine learning, human-computer interaction, and AI ethics to develop innovative solutions that can be practically applied in real-world scenarios. We foster an environment of intellectual curiosity, collaboration, and innovation. We encourage our researchers to explore new ideas, engage in open discussions, and contribute to the wider AI community through publications and conference presentations. Our goal is to be at the forefront of human-centric AI development, setting new standards for how AI systems learn from and interact with humans.Labelbox strives to ensure pay parity across the organization and discuss compensation transparently.  The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.Annual base salary range$250,000—$300,000 USDLife at Labelbox Location: Join our dedicated tech hubs in San Francisco or Wrocław, Poland Work Style: Hybrid model with 2 days per week in office, combining collaboration and flexibility Environment: Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making Growth: Career advancement opportunities directly tied to your impact Vision: Be part of building the foundation for humanity's most transformative technology Our Vision We believe data will remain crucial in achieving artificial general intelligence. As AI models become more sophisticated, the need for high-quality, specialized training data will only grow. Join us in developing new products and services that enable the next generation of AI breakthroughs. Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins. Our customers include Fortune 500 enterprises and leading AI labs. Your Personal Data Privacy: Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice. Any emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications.

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What is Findem: Findem is HR 2.0. We’re a fast-growth startup with an ambitious vision and the technology to back it up. Our People Intelligence platform uses true AI and machine learning to provide critical solutions for talent acquisition and people analytics functions. With the deep insights that our platform provides, companies can build more engaged and diverse teams, and close their talent gaps faster. We have an amazing opportunity to establish ourselves as leaders in this space, and we need strong advocates to help us achieve that goal. We’re backed by top-tier investors including Wing Venture Capital – the same firm that backed Snowflake, Cohesity, and Gong. Findem powers businesses across scaling, pre-IPO, and publicly traded companies who trust us to solve their biggest HR and Talent challenges. We have an incredibly skilled and collaborative team that values curiosity, diversity, openness and building great experiences every day for our customers. Our PM team tends to attract scrappy, collaborative, high-ownership, customer-driven innovators. Emojis, jokes, and pet pictures flow freely in our Slack. Why We Need You: We’re looking for a seasoned Principal Product Manager who can lead one of the most important bets for the company. This role will lead this initiative, including setting strategy / KPIs, driving product choices and delivering high impact. You will be comfortable getting hands-on with detailed, nuanced product choices, while also understanding the larger path ahead with your overall strategy. Finally, to land a great outcome, you will need to be an excellent cross-functional collaborator. What You'll Do:Scope: Lead a major product at Findem, including setting long-term strategy, and making the business case for more investmentInsights: Own the company’s thesis for the market segment including the target buyer and customer personas and their most important needsProduct craft: Bring robust, first-principle, out of the box thinking to our problem space, and using quantitative and qualitative data to drive your conclusionsCrafted execution: Work closely with engineering to focus our efforts on the most impactful innovations, owning prioritization, unblocking major issues, and landing product milestonesCommunication: Working cross-functionally with marketing, GMs, support, and other stakeholders to drive alignment to the right goals. Your Working Experience:7+ years as a product manager, ideally with startup experienceExperience doing 0->1 and 1->10 product buildingExperience in with B2B PLG products, B2B SaaS (especially for multi-step workflows)Ability to drive short term execution while building towards (and testing) a long term vision What Makes You a Great Fit:Prior experience with assisting or automating manual workflowsPrior experience in recruiting or HR softwarePrior experience in AI/ML products

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Why Casca?Casca is building AGI for banking. We’re replacing decades-old legacy systems with AI-native technology that automates 90% of the manual work humans once had to do. As our founding PM, you'll define and drive Casca's end-to-end product development. We're not just building features—we're creating an entirely new way for banks to operate. You'll collaborate directly with our business & engineering team to transform complex AI capabilities into elegant solutions that make legacy banking systems obsolete. This is a rare opportunity to shape a category-defining product at the intersection of AI and finance. What you'll do:Lead End-to-End Product DevelopmentOversee the product development lifecycle from concept to release, ensuring alignment with Casca’s strategic goals.Define clear product roadmaps based on stakeholder input and user feedback.Drive product development with subject matter experts and designer partners. Lead feature release management & user training materials. Product User ExperienceChampion user-centric design by ensuring products are intuitive, user-friendly, and meet the highest quality standards.Translate complex AI capabilities into simple, transparent user experiences that delight customers.Strategize & InnovateDrive the product vision and strategy by thinking outside the box to deliver AI-native solutions that set new industry standards.Continuously explore emerging technologies and industry trends to keep Casca ahead of the curve.Cross-Functional CollaborationPartner with engineering, design, marketing, and sales teams to deliver a best-in-class product experience.Facilitate effective communication and coordination across teams to ensure timely and successful product launches.What you'll bring:Experience: 4+ years of proven experience as a Product Manager or Product Lead in a fast-paced, tech-driven environment, preferably delivered customer-facing AI technology or financial service products. Technical background: Degree in Computer Science or experience as an engineer preferredAI & Financial Domain Knowledge: Familiarity with AI, machine learning, and/or financial services is highly desirable.Strategic Thinking: Demonstrated ability to think creatively, innovate, and challenge the status quo to develop unique, differentiated products.Cross-Functional Leadership: Excellent communication, collaboration, and influencing skills across diverse teams.Analytical Skills: Strong analytical and problem-solving abilities with a data-driven approach to decision-making.Adaptability: Ability to manage multiple priorities, pivot quickly, and thrive in a dynamic startup environment.What you'll get: Impact & Ownership: A unique opportunity to shape the future of banking through AI, owning end-to-end product initiatives.Collaborative Environment: Work alongside a talented and passionate team that values continuous improvement and knowledge sharing.Competitive Compensation: Includes salary, benefits, and potential equity in a fast-growing startup.Professional Growth: Access to resources and mentorship to expand your skill set, influence strategy, and accelerate your career.Culture of Innovation: We encourage risk-taking, learning from failures, and pushing the boundaries of what’s possible in fintech.As an early-stage company building at the frontier of AI, we work with high intensity and commitment. While schedules can vary by role/team, many weeks will demand extra focus, flexibility and time particularly during major launches and high impact sprints. We're seeking those who are aligned to and able to commit to that expectation which includes 5 days per week in our San Francisco Office.

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Ironclad is the leading AI-powered contract lifecycle management platform, processing billions of contracts every year. Every business is powered by contracts, but managing them can slow companies down and cost millions of dollars. Global innovators like L’Oréal, OpenAI, and Salesforce trust Ironclad to transform contracting into a strategic advantage - accelerating revenue, reducing risk, and driving efficiency. It’s the only platform that manages every type of contract workflow, whether a sales agreement, an HR agreement or a complex NDA. We’re building the future of intelligent contracting and writing the narrative for how contracts unlock strategic growth. Forrester Wave and Gartner Magic Quadrant have consistently recognized Ironclad as a leader in our category. We’ve also been named one of Fortune’s Great Places to Work six years running, featured on Glassdoor’s Best Places to Work, and recognized by Forbes’ 50 Most Promising AI Companies. We’re backed by leading investors like Accel, Sequoia, Y Combinator, and BOND. We’d love for you to join us! Solutions Engineers @ IroncladSolution Engineers (SEs) are Ironclad Sales Team’s pre-sale technical experts. SEs collaborate closely with prospects and Ironclad’s Sales, Implementation, and Product teams, forming a critical technical overlay to the sales and solution evaluation.At Ironclad, SEs are creative, value-driven technology experts that love to engage with people. They drive sales through clear communication focusing on customer use cases, technology infrastructure, and solution design. With a comprehensive understanding of Ironclad’s platform, SEs empower prospects to understand how Ironclad can work for them.SEs also help Ironclad improve our platform: the best SEs help capture the most challenging technical requirements observed in the market and translate them into actionable insights for Ironclad’s Product team to develop.Requirements, you must be:Mission-oriented: You’re excited to work on a team that operates at the intersection of human talent and software; you want to put that passion to work in an industry that still skews heavily towards human/manual work. You want to work at a place where you can have an outsized impact.Exceptional communicator: You’re a strong verbal communicator, able to capture an audience with clear and confident language. You can understand and empathize with people even if you have limited subject-matter knowledge of their area of expertise.Technically proficient: You’re an expert at technical configuration and familiar with or have an appetite for learning programming languages such as JSON, HTML and, ideally, JavaScript or similar languages. You recognize that your ability and willingness to develop these skills is an important part of what makes SEs successful in their role as Ironclad’s prospect-facing solution experts.Creative problem solver: You listen well and understand customers' needs. You think outside the box to solve their challenges and deliver a solution that will drive value for the customer.Team player: You can work effectively in teams of technical and non-technical individuals. You are energized by collaborating with diverse teams.Independent: You can learn and drive outcomes with minimal supervision. You have a bias toward action and gravitate towards environments where you have an outsized influence on the success of outcomes for customers and colleagues. You are exceptionally good at making trade-offs based on incomplete data.Experience: 3+ years of Solution Engineering experience. Experience in AI and LLM-based applications.Responsibilities:Listen to prospects' needs and goals. Listening is our #1 strength.Design, build and present custom demonstrations of the Ironclad platform using a prospect’s own contracts and workflows.Build strong relationships with prospects to help Ironclad’s most important and strategic prospects evaluate and ultimately select Ironclad.Collaborate with Account Executives and other internal partners to progress an evaluation forward smoothly.Bring actionable insights back to Ironclad’s Product Team to help us evolve our core product.Partner with your aligned Sales Leader to support pipeline generating activities and overall team success Benefits:Health, dental, and vision insurance401kWellness reimbursementTake what you need vacation policyGenerous parental leave for both primary and secondary caregiversOTE Range: $160,000 - $190,000The OTE range represents the minimum and maximum of the OTE range for this position based at our San Francisco headquarters. The OTE offered for this position will depend on numerous factors, including individual proficiency, anticipated performance, and the location of the selected candidate. Our OTE is just one component of Ironclad’s competitive total rewards package, which also includes equity awards (a new hire grant, along with opportunities for additional awards throughout your tenure), competitive health and wellness benefits, and a commitment to career growth and development. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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About FirsthandFirsthand has built the first AI-powered Brand Agent platform, transforming the way marketers and publishers engage consumers through their own AI agents, anywhere online.While most AI applications in marketing and advertising focus on back-office automation, the Firsthand Brand Agent Platform™ powers front-line consumer engagement. Operating across both owned properties and paid media, Firsthand's Brand Agents make a company’s expertise accessible in real time, adapting to consumers’ interests and guiding them towards the information they need to take action. Central to the platform is Lakebed™, the company’s AI-first data and knowledge rights management system that ensures brands retain full ownership and control of their expertise.Firsthand is led by Jon Heller, Michael Rubenstein, and Wei Wei, whose previous ventures helped build the foundations of modern digital advertising. Backed by Radical Ventures, FirstMark Capital, Aperiam Ventures, and Crossbeam Venture Partners, Firsthand is shaping the future of AI-driven consumer engagement.Firsthand is headquartered in NYC, with team members working together in-office three days a week.Firsthand is looking to hire a Senior Director, Marketer Sales to drive adoption of Brand Agents with senior marketers at the world’s leading brands.In this pivotal role, you'll educate, evangelize, and drive adoption of a transformative new marketing model: “agents, not ads.” You’ll lead strategic sales to brand-side marketing executives, serve as a consultative partner across innovation and media teams, and help fully commercialize Firsthand’s marketer offering. You'll also collaborate across Firsthand’s buyside motions, supporting publisher campaigns and identifying strategic agency partnerships.You are a seasoned commercial leader with a strong grasp of marketing, media, and technology. You bring experience in ad networks or programmatic, the ability to navigate complex organizations, and the entrepreneurial mindset to shape the offering as you sell it. You're comfortable engaging both business and technical stakeholders and thrive in early-stage environments where the path isn't fully paved.The ideal candidate will be located in the New York metropolitan area. Key ResponsibilitiesLead strategic marketer engagements: Act as the point person for existing marketer-direct relationships, advancing relationships and identifying opportunities to deepen impact.Drive the direct-to-marketer motion: Engage CMOs, Heads of Innovation, and digital marketing leaders to position Brand Agents as a strategic lever for long-term brand and consumer engagement.Develop the marketer offering: Help define and operationalize Firsthand’s holistic offering for marketers, contributing to early commercialization strategy, vertical prioritization, product feedback, and business model development (pricing, contracts, implementation).Lead strategic pitches: Own and lead marketer-focused pitches to build the 2026 pipeline.Collaborate across publisher and agency motions: Partner with internal teams to identify leverage points across publisher demand and emerging agency relationships.Run a disciplined pipeline: Forecast accurately, manage multi-stakeholder deals with rigor, and close high-value opportunities.Act as a strategic partner: Provide structured insights to product and leadership teams to inform positioning, vertical strategy, and GTM readiness.Qualifications10+ years of sales experience, ideally across martech, adtech, or mediaTrack record of success selling to brand-side marketers at large, matrixed organizationsExperience working in or closely with ad networks and programmatic platforms; understanding of agency dynamics a plusAbility to engage both technical and marketing stakeholders, including product, data, and legal counterpartsComfortable in early-stage, pioneering environments; you know how to shape a product while selling itStrategic, scrappy, and adaptive, with strong communication skills and executive presenceEntrepreneurial mindset: excited to help build and refine the offering—not just run the playbookHow to ApplyIf you are ready to embark on an exhilarating journey at the forefront of AI, seize this incredible opportunity and apply here. We eagerly anticipate hearing from you!Note: Compensation and equity will be market-competitive for well-capitalized, early stage startups and will be discussed during the interview process.

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Who We Are PathAI is on a mission to improve patient outcomes with AI-powered pathology. We are transforming traditional pathology methods into powerful, new technologies. These innovations in pathology can help accelerate drug development, improve confidence in the accuracy of diagnosis, and get life-saving therapies to patients more quickly. At PathAI, you'll work with a diverse and talented team of people, who are dedicated to solving complex problems and making a huge impact. Where You Fit  We're looking for a technical product manager to join our team and help support the execution of PathAI’s product roadmap. The AI Product Manager will work closely with machine learning, pathology, biomedical data science, clinical affairs, quality, regulatory, and business operations teams to ensure that product development goals are being met for successful delivery of a product. The successful candidate will be able to identify, build, and champion AI products in key strategic areas for PathAI.   This role offers the opportunity to help define the product strategy of a fast growing, dynamic business. What You’ll Do Contribute to the development of the roadmap for PathAI algorithm products within a key business unit or disease area, and own the execution of assigned initiatives. Collaborate with stakeholders to gather requirements, define priorities, and align on product direction. Support the development of business cases for new products, product extensions, or platform capabilities. Partner cross-functionally with product designers, engineers, and scientists to deliver high-quality solutions that meet user needs. Monitor product performance, gather feedback, and contribute to continuous improvement initiatives. What You Bring  3+ years experience in product management (preferably bioinformatics, machine learning, or data science). Launch experience with algorithm-based products in life sciences and/or healthcare. Advanced degree in computational biology, biomedical engineering, biology, or related field preferred Experience contributing to the launch of AI-driven or software-based products. Strong collaboration skills and ability to work with cross-functional teams across technical and scientific domains. Curiosity and willingness to learn about oncology, pathology, and AI-powered products. We Want To Hear From You At PathAI, we are looking for individuals who are team players, are willing to do the work no matter how big or small it may be, and who are passionate about everything they do. If this sounds like you, even if you may not match the job description to a tee, we encourage you to apply. You could be exactly what we're looking for.  PathAI is an equal opportunity employer, dedicated to creating a workplace that is free of harassment and discrimination. We base our employment decisions on business needs, job requirements, and qualifications — that's all. We do not discriminate based on race, gender, religion, health, personal beliefs, age, family or parental status, or any other status. We don't tolerate any kind of discrimination or bias, and we are looking for teammates who feel the same way. 

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About Anyscale: At Anyscale, we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray, a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI, Uber, Spotify, Instacart, Cruise, and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the roleAs a Member of Technical Staff, Field Eng at Anyscale, you will be the technical face of our company and biggest advocate for our customers. You’ll work closely with sales, product management, and engineering to ensure that our product has the right experiences and shape to drive value in customer engagements.  The ideal candidate will be a scrappy executor, able to work independently, and lead complex POVs with our users as they adopt Anyscale and Ray. You’ll be on point for demoing our product, scoping POVs, making users successful, and amplifying the voice of our customers. Expect to learn a ton about Ray, Anyscale, and early stage product go-to-market! You’ll be fundamental in helping us disrupt what it means to build distributed applications at scale.  Our product is inherently technical, so we’re looking for folks that know how to communicate about technical products with multiple audiences – whether it’s the C-suite or an individual engineer.As part of this role, you'll be involved inBuilding awesome product demos, tutorials, reference architectures, and blogs demonstrating the strong capabilities of the Anyscale platformKnowing Ray from end-to-end and educating customers on how to use RayWorking with customers as they build applications on RayKnowing the ML landscape and toolsets that are at the forefront of cutting edge techWorking cross-functionally to be the voice of our customers and delivering impactful solutions alongside our product and engineering teams Working directly with customers at every layer of their organization (C Suite to data scientists and developers) and acting as a trusted advisor for our usersHelping us identify potential improvements and gaps in our product and prioritizing features through the development processEfficiently managing stakeholders to ensure that we stay focused on our key objective and metrics in the sales processDriving crisp communication about our products and services, both internally and externallyWorking alongside marketing and Go-to-Market to create and deliver high quality content to evangelize Anyscale and RayWe'd love to hear from you if you have5+ years of pre- and post-sales experience, either as a sales engineer, solutions engineer, architect, customer success engineer/manager, or a consultantStrong technical skills. You should have working knowledge of Python fundamentals, as well as the ability to learn Ray and build Ray applications with various librariesExperience in enterprise SaaS, infrastructure, open source, and/or ML/AI technologiesExperience in public cloud and enterprise infrastructureCustomer success orientation. You are able to demonstrate technical concepts to technical and non-technical audiences, build value with end users, and drive solutions over the lineCross-functional collaboration with technical stakeholders, including Engineering and ProductCompensation:At Anyscale, we take a market-based approach to compensation. We are data-driven, transparent, and consistent.  As the market data changes over time, the target salary for this role may be adjusted. This role is also eligible to participate in Anyscale's Equity and Benefits offerings, including the following:Stock OptionsHealthcare plans, with premiums covered by Anyscale at 99% for both employees and dependents401k Retirement PlanEducation & Wellbeing StipendPaid Parental LeaveFertility BenefitsPaid Time OffCommute reimbursement100% of in-office meals coveredAnyscale Inc. is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law.  Anyscale Inc. is an E-Verify company and you may review the Notice of E-Verify Participation and the Right to Work posters in English and Spanish

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About Us Observe.AI enables enterprises to transform how they connect with customers - through AI agents and copilots that engage, assist, and act across every channel. From automating conversations to guiding human agents in real time to uncovering insights that shape strategy, Observe.AI turns every interaction into a driver of loyalty and growth. Trusted by global leaders, we’re creating a future where every customer experience is smarter, faster, and more impactful. Why Join Us The future of customer engagement is AI-driven, with conversational automation representing a $300B market opportunity. While traditional NLP/NLU-powered solutions have fallen short, Observe.AI is leading the revolution with state-of-the-art LLM-powered Conversational AI technology. Backed by 7 years of experience and insights from 300+ customers, we’re perfectly positioned to disrupt the space and unlock massive value for enterprises worldwide. We are seeking an Implementation Manager who will be responsible for project managing, facilitating stakeholder design workshops, building out customer use-cases discovered during onboarding, and delivering virtual/onsite software training to trainer and end-user audiences. The implementation manager will work with new customers to stand up their Observe.AI programs and existing customers to expand their capabilities with the Observe.AI product suite. This role will need to quickly learn and adapt the customer's business objectives into a successful onboarding process from sales handoff to CSM transition. The ideal candidate applies their SaaS experience to driving implementation projects to completion, engaging key stakeholders to build a strong program foundation, and communicating technical and functional concepts in a clear concise manner. As a key member of our core team, you’ll play a pivotal role in implementing and launching cutting-edge Conversational AI products. You’ll work at the forefront of AI innovation, helping to build solutions that will transform how global enterprises adopt and scale AI—delivering real-time customer assistance, smarter automation, and seamless interactions. This is your chance to join an industry leader as we drive the future of Conversational AI and empower enterprises to reach new levels of efficiency and customer satisfaction. What you’ll be doing Lead a customer program team through a multi-phase implementation involving business discovery, technical setup, and user training Guide and enable customers on their contact center AI journey with our software Deliver tailored customer training sessions across a variety of formats (e.g. live, recorded, virtual, in-person, train-the-trainer, end-user) Manage client expectations, project timelines, documentation deliverables, and team resources Partner with CSMs to create value-based adoption goals that set the Customer up for a successful launch Communicate project status, issues, and risks while escalating effectively as appropriate Manage multiple customer projects simultaneously Collaborate cross-functionally with Sales, Product, Marketing, and Customer Success to improve services delivery and customer experience What you'll bring to the role 5+ years of work experience implementing SaaS software Comfort in user-centered communications and facilitating technical problem solving Basic understanding of speech analytics and quality management software and processes Experience in a customer-facing role with clear deliverables and stakeholder management Proficiency in coaching and facilitation skills Training experience is highly preferred Demonstrable analytical, problem-solving, and time management skills Experience in the Software & Platform industry Experience managing complex customer implementations Perks & Benefits Competitive compensation including equity Excellent medical, dental, and vision insurance options Flexible time off  10 Company holidays + Winter Break and up to 16-weeks of parental leave 401K plan Quarterly Lifestyle Spend Monthly Mobile + Internet Stipend Pre-tax Commuter Benefits Salary Range The base salary compensation range targeted for this full-time position is $100,000 - $135,000 per annum. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives and equity (in the form of options). This salary range is an estimate, and the actual salary may vary based on the Company’s compensation practices. Our Commitment to Inclusion and Belonging Observe.AI is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Observe AI does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Observe.AI also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. We welcome all people. We celebrate diversity of all kinds and are committed to creating an inclusive culture built on a foundation of respect for all individuals. We seek to hire, develop, and retain talented people from all backgrounds. Individuals from non-traditional backgrounds, historically marginalized or underrepresented groups are strongly encouraged to apply. If you are ambitious, make an impact wherever you go, and you're ready to shape the future of Observe.AI, we encourage you to apply. For more information, visit www.observe.ai. #LI-REMOTE

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About Faculty At Faculty, we transform organisational performance through safe, impactful and human-centric AI. With more than a decade of experience, we provide over 350 global customers with software, bespoke AI consultancy, and Fellows from our award winning Fellowship programme. Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI. Should you join us, you’ll have the chance to work with, and learn from, some of the brilliant minds who are bringing Frontier AI to the frontlines of the world.We operate a hybrid way of working, meaning that you'll split your time across client location, Faculty's Old Street office and working from home depending on the needs of the project. For this role, you can expect to be client-side for up-to three days per week at times and working either from home or our Old street office for the rest of your time. What You'll Be DoingWorking in our Defence business unit You will design, build, and deploy production-grade software, infrastructure, and MLOps systems that leverage machine learning. The work you do will help our customers solve a broad range of high-impact problems in the defence and national security space - examples of which can be found hereYou are engineering-focused, with a keen interest and working knowledge of operationalised machine learning. You have a desire to take cutting-edge ML applications into the real world. You will develop new methodologies and champion best practices for managing AI systems deployed at scale, with regard to technical, ethical and practical requirements. You will support both technical and non-technical stakeholders to deploy ML to solve real-world problems. To enable this, we work in cross-functional teams with representation from commercial, data science, product management and design specialities to cover all aspects of AI product delivery.The Machine Learning Engineering team is responsible for the engineering aspects of our customer delivery projects. As a Machine Learning Engineer, you’ll be essential to helping us achieve that goal by:Building software and infrastructure that leverages Machine Learning;Creating reusable, scalable tools to enable better delivery of ML systemsWorking with our customers to help understand their needsWorking with data scientists and engineers to develop best practices and new technologies; andImplementing and developing Faculty’s view on what it means to operationalise ML software.We’re a rapidly growing organisation, so roles are dynamic and subject to change. Your role will evolve alongside business needs, but you can expect your key responsibilities to include: Working in cross-functional teams of engineers, data scientists, designers and managers to deliver technically sophisticated, high-impact systems.Leading on the scope and design of projectsOffering leadership and management to more junior engineers on the team Providing technical expertise to our customersTechnical DeliveryWho We're Looking ForAt Faculty, your attitude and behaviour are just as important as your technical skill. We look for individuals who can support our values, foster our culture, and deliver for our organisation.We like people who combine expertise and ambition with optimism -- who are interested in changing the world for the better -- and have the drive and intelligence to make it happen. If you’re the right candidate for us, you probably:Think scientifically, even if you’re not a scientist - you test assumptions, seek evidence and are always looking for opportunities to improve the way we do things.Love finding new ways to solve old problems - when it comes to your work and professional development, you don’t believe in ‘good enough’. You always seek new ways to solve old challenges.Are pragmatic and outcome-focused - you know how to balance the big picture with the little details and know a great idea is useless if it can’t be executed in the real world.To succeed in this role, you’ll need the following - these are illustrative requirements and we don’t expect all applicants to have experience in everything (70% is a rough guide):Understanding of and interest in the full machine learning lifecycle, including deploying trained machine learning models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorchUnderstanding of the core concepts of probability and statistics and familiarity with common supervised and unsupervised learning techniquesExperience in Software Engineering including programming in Python.Technical experience of cloud architecture, security, deployment, and open-source tools. Hands-on experience required of at least one major cloud platformDemonstrable experience with containers and specifically Docker and KubernetesComfortable in a high-growth startup environment.Outstanding verbal and written communication.Excitement about working in a dynamic role with the autonomy and freedom you need to take ownership of problems and see them through to executionWhat we can offer you: The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day. Faculty is the professional challenge of a lifetime. You’ll be surrounded by an impressive group of brilliant minds working to achieve our collective goals. Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you’ll learn something new from everyone you meet.

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At Parallel Web Systems, we are bringing a new web to life: it’s built with, by, and for AIs. Our work spans innovations across crawling, indexing, ranking, retrieval, and reasoning systems. Our first product is a set of APIs for AIs to do more with web data. We are a fully in-person team based in Palo Alto, CA. Our organization is flat; our team is small and talent dense.We want to talk to you if you are someone who can bring us closer to living our aspirational values:Own customer impact - It’s on us to ensure real-world outcomes for our customers.Obsess over craft - Perfect every detail because quality compounds.Accelerate change - Ship fast, adapt faster, and move frontier ideas into production.Create win-wins - Creatively turn trade-offs into upside.Make high-conviction bets - Try and fail. But succeed an unfair amount.Job: You will build, operate, and scale our infrastructure, including our infrastructure around large language models, and ensure that our systems are reliable and cost-efficient as we grow. You will anticipate bottlenecks before they appear, ensure that our architecture evolves to meet increasing demands, and build the tools and systems that keep engineering velocity high.You: Have deep intuition on distributed systems, cloud platforms, performance tuning, and scalable architecture. You like to reason about trade-offs between cost, reliability, and speed of iteration. You care about your work enabling every team to build faster and ship confidently, and about infrastructure that can support products used by millions without breaking a sweat.Our founder is Parag Agrawal. Previously, he was the CEO and CTO at Twitter. Our investors include First Round Capital, Index Ventures, Khosla Ventures, and many others.

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About DecagonDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experience. Our AI agents provide intelligent, human-like responses across chat, email, and voice, resolving millions of customer inquiries across every language and at any time.Since coming out of stealth, Decagon has experienced rapid growth. We partner with industry leaders like Hertz, Eventbrite, Duolingo, Oura, Bilt, Curology, and Samsara to redefine customer experience at scale. We've raised over $200M from Bain Capital Ventures, Accel, a16z, BOND Capital, A*, Elad Gil, and notable angels such as the founders of Box, Airtable, Rippling, Okta, Lattice, and Klaviyo.We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values—customers are everything, relentless momentum, winner’s mindset, and stronger together—shape how we work and grow as a team.About the TeamOver the past few years, development of LLMs has evolved at a rapid pace. It’s not enough for our customers to just “set it and forget it” when it comes to AI software. Truly successful AI Agents require guidance and input throughout the development lifecycle.The Agent Product Management team drives this journey as Decagon’s in-house experts on building, deploying, and scaling AI agents. Agent PMs work directly with customers to bring their AI agents to life, and then grow each Agent into a core part of each company’s businesses. As one of our early APM’s, you will deploy our technology into some of the world’s most influential businesses, driving real world business impact as one part Product Manager, one part AI expert.The APM owns each step in the AI Agent build lifecycle. This can include:Collaborating with engineering to design a new product featureWriting and testing prompt logic for a specific customer use caseWorking with a customer’s executive team to define their AI roadmapYou’ll partner closely with every team at Decagon: Go-To-Market, Design, Engineering, and across our leadership team. You will own and drive your customer builds and help shape the overall product roadmap by being the voice of the customer.About the RoleWe’re looking for a Strategic APM that thrives in a highly autonomous environment. You’re product-minded, scrappy, can drive highly complex projects across cross-functional teams, and are comfortable building relationships with some of the largest brands in the world.Given their size, these strategic accounts often present the challenge of complexity, requiring the navigation of customer stakeholders across org charts. A successful Strat APM will be able to navigate this complexity seamlessly and develop deep, trusted relationships with key stakeholders at all levels of the customer organization (comfortable speaking to CX leaders, Product Leaders, and Operations Leaders).APMs at Decagon own their own portfolio of agents from end-to-end and are trusted to make real impact. You’ll have the opportunity to dive deep into complex business problems, build elegant solutions and then scale them out to millions users, all while being part of the founding Strat APM team. This role is ideal for future founders, general managers, and business unit leaders.In this role, you willBuild, Design and optimize Enterprise-quality AI agents in collaboration with Decagon’s most strategic customers — understanding their workflows, pain points, and goals.Embed deeply within strategic customers to understand their business challenges and serve as a strategic advisor to their AI roadmapRun tight feedback loops into Engineering — influence feature development based on real customer needs.Represent Decagon externally — working closely with customers and prospects, participating in key deployments.Collaborate closely with Decagon’s C-suite and other executives to continue building the playbook for strategic logos for DecagonYour background looks something like thisHave 8+ years of relevant experience. This includes but is not limited to:Senior manager or equivalent at a top-tier consulting or other professional services firmPartner at an investing firmSenior product leader or group product managerDeep technical acumen — able to understand and shape AI agent designs.Strong communication and relationship-building skills.Comfort working in fast-moving, ambiguous environments where you shape solutions as much as you implement them.Even betterA Computer Science, Engineering, or Math degree — or equivalent technical experience.An MBABenefitsMedical, dental, and vision benefitsTake what you need vacation policyDaily lunches, dinners and snacks in the office to keep you at your bestCompensation$240K – $285K + Offers Equity

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About DecagonDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experience. Our AI agents provide intelligent, human-like responses across chat, email, and voice, resolving millions of customer inquiries across every language and at any time.Since coming out of stealth, Decagon has experienced rapid growth. We partner with industry leaders like Hertz, Eventbrite, Duolingo, Oura, Bilt, Curology, and Samsara to redefine customer experience at scale. We've raised over $200M from Bain Capital Ventures, Accel, a16z, BOND Capital, A*, Elad Gil, and notable angels such as the founders of Box, Airtable, Rippling, Okta, Lattice, and Klaviyo.We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values—customers are everything, relentless momentum, winner’s mindset, and stronger together—shape how we work and grow as a team.About the TeamOver the past few years, development of LLMs has evolved at a rapid pace. It’s not enough for our customers to just “set it and forget it” when it comes to AI software. Truly successful AI Agents require guidance and input throughout the development lifecycle.The Agent Product Management team drives this journey as Decagon’s in-house experts on building, deploying, and scaling AI agents. Agent PMs work directly with customers to bring their AI agents to life, and then grow each Agent into a core part of each company’s businesses. As one of our early APM’s, you will deploy our technology into some of the world’s most influential businesses, driving real world business impact as one part Product Manager, one part AI expert.The APM owns each step in the AI Agent build lifecycle. This can include:Collaborating with engineering to design a new product featureWriting and testing prompt logic for a specific customer use caseWorking with a customer’s executive team to define their AI roadmapYou’ll partner closely with every team at Decagon: Go-To-Market, Design, Engineering, and across our leadership team. You will own and drive your customer builds and help shape the overall product roadmap by being the voice of the customer.About the RoleWe’re looking for a Strategic APM that thrives in a highly autonomous environment. You’re product-minded, scrappy, can drive highly complex projects across cross-functional teams, and are comfortable building relationships with some of the largest brands in the world.Given their size, these strategic accounts often present the challenge of complexity, requiring the navigation of customer stakeholders across org charts. A successful Strat APM will be able to navigate this complexity seamlessly and develop deep, trusted relationships with key stakeholders at all levels of the customer organization (comfortable speaking to CX leaders, Product Leaders, and Operations Leaders).APMs at Decagon own their own portfolio of agents from end-to-end and are trusted to make real impact. You’ll have the opportunity to dive deep into complex business problems, build elegant solutions and then scale them out to millions users, all while being part of the founding Strat APM team. This role is ideal for future founders, general managers, and business unit leaders.In this role, you willBuild, Design and optimize Enterprise-quality AI agents in collaboration with Decagon’s most strategic customers — understanding their workflows, pain points, and goals.Embed deeply within strategic customers to understand their business challenges and serve as a strategic advisor to their AI roadmapRun tight feedback loops into Engineering — influence feature development based on real customer needs.Represent Decagon externally — working closely with customers and prospects, participating in key deployments.Collaborate closely with Decagon’s C-suite and other executives to continue building the playbook for strategic logos for DecagonYour background looks something like thisHave 8+ years of relevant experience. This includes but is not limited to:Senior manager or equivalent at a top-tier consulting or other professional services firmPartner at an investing firmSenior product leader or group product managerDeep technical acumen — able to understand and shape AI agent designs.Strong communication and relationship-building skills.Comfort working in fast-moving, ambiguous environments where you shape solutions as much as you implement them.Even betterA Computer Science, Engineering, or Math degree — or equivalent technical experience.An MBABenefitsMedical, dental, and vision benefitsTake what you need vacation policyDaily lunches, dinners and snacks in the office to keep you at your bestCompensation$240K – $285K + Offers Equity

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Company OverviewDeepgram is the leading voice AI platform for developers building speech-to-text (STT), text-to-speech (TTS) and full speech-to-speech (STS) offerings. 200,000+ developers build with Deepgram’s voice-native foundational models – accessed through APIs or as self-managed software – due to our unmatched accuracy, latency and pricing. Customers include software companies building voice products, co-sell partners working with large enterprises, and enterprises solving internal voice AI use cases. The company ended 2024 cash-flow positive with 400+ enterprise customers, 3.3x annual usage growth across the past 4 years, over 50,000 years of audio processed and over 1 trillion words transcribed. There is no organization in the world that understands voice better than DeepgramThe OpportunityVoice is the most natural modality for human interaction with machines. However, current sequence modeling paradigms based on jointly scaling model and data cannot deliver voice AI capable of universal human interaction. The challenges are rooted in fundamental data problems posed by audio: real-world audio data is scarce and enormously diverse, spanning a vast space of voices, speaking styles, and acoustic conditions. Even if billions of hours of audio were accessible, its inherent high dimensionality creates computational and storage costs that make training and deployment prohibitively expensive at world scale. We believe that entirely new paradigms for audio AI are needed to overcome these challenges and make voice interaction accessible to everyone. The RoleAs a Member of the Research Staff, you will pioneer the development of Latent Space Models (LSMs), a new approach that aims to solve the fundamental data, scale, and cost challenges associated with building robust, contextualized voice AI. Your research will focus on solving one or more of the following problems:Build next-generation neural audio codecs that achieve extreme, low bit-rate compression and high fidelity reconstruction across a world-scale corpus of general audio.Pioneer steerable generative models that can synthesize the full diversity of human speech from the codec latent representation, from casual conversation to highly emotional expression to complex multi-speaker scenarios with environmental noise and overlapping speech.Develop embedding systems that cleanly factorize the codec latent space into interpretable dimensions of speaker, content, style, environment, and channel effects -- enabling precise control over each aspect and the ability to massively amplify an existing seed dataset through “latent recombination”.Leverage latent recombination to generate synthetic audio data at previously impossible scales, unlocking joint model and data scaling paradigms for audio.  Endeavor to train multimodal speech-to-speech systems that can 1) understand any human irrespective of their demographics, state, or environment and 2) produce empathic, human-like responses that achieve conversational or task-oriented objectives.   Design model architectures, training schemes, and inference algorithms that are adapted for hardware at the bare metal enabling cost efficient training on billion-hour datasets and powering real-time inference for hundreds of millions of concurrent conversations.The ChallengeWe are seeking researchers who:See "unsolved" problems as opportunities to pioneer entirely new approachesCan identify the one critical experiment that will validate or kill an idea in days, not monthsHave the vision to scale successful proofs-of-concept 100xAre obsessed with using AI to automate and amplify your own impactIf you find yourself energized rather than daunted by these expectations—if you're already thinking about five ideas to try while reading this—you might be the researcher we need. This role demands obsession with the problems, creativity in approach, and relentless drive toward elegant, scalable solutions. The technical challenges are immense, but the potential impact is transformative. It's Important to Us That You HaveStrong mathematical foundation in statistical learning theory, particularly in areas relevant to self-supervised and multimodal learningDeep expertise in foundation model architectures, with an understanding of how to scale training across multiple modalitiesProven ability to bridge theory and practice—someone who can both derive novel mathematical formulations and implement them efficientlyDemonstrated ability to build data pipelines that can process and curate massive datasets while maintaining quality and diversityTrack record of designing controlled experiments that isolate the impact of architectural innovations and validate theoretical insightsExperience optimizing models for real-world deployment, including knowledge of hardware constraints and efficiency techniquesHistory of open-source contributions or research publications that have advanced the state of the art in speech/language AI How We Generated This Job DescriptionThis job description was generated in two parts.  The “Opportunity”, “Role”, and “Challenge” sections were generated by a human using Claude-3.5-sonnet as a writing partner.  The objective of these sections is to clearly state the problem that Deepgram is attempting to solve, how we intend to solve it, and some guidelines to help you decide if Deepgram is right for you. Therefore, it is important that this section was articulated by a human.  The “It’s Important to Us” section was automatically derived from a multi-stage LLM analysis (using o1) of key foundational deep learning papers related to our research goals.  This work was completed as an experiment to test the hypothesis that traits of highly productive and impactful researchers are reflected directly in their work. The analysis focused on understanding how successful researchers approach problems, from mathematical foundations through to practical deployment. The problems Deepgram aims to solve are immensely difficult and span multiple disciplines and specialties. As such, we chose seminal papers that we believe reflect the pioneering work and exemplary human characteristics needed for success. The LLM analysis culminates in an “Ideal Researcher Profile”, which is reproduced below along with the list of foundational papers.  Ideal Researcher ProfileAn ideal researcher, as evidenced by the recurring themes across these foundational papers, excels in five key areas: (1) Statistical & Mathematical Foundations, (2) Algorithmic Innovation & Implementation, (3) Data-Driven & Scalable Systems, (4) Hardware & Systems Understanding, and (5) Rigorous Experimental Design. Below is a synthesis of how each paper highlights these qualities, with references illustrating why they matter for building robust, impactful deep learning models. 1. Statistical & Mathematical FoundationsMastery of Core ConceptsMany papers, like Scaling Laws for Neural Language Models and Neural Discrete Representation Learning (VQ-VAE), reflect the importance of power-law analyses, derivation of novel losses, or adaptation of fundamental equations (e.g., in VQ-VAE's commitment loss or rectified flows in Scaling Rectified Flow Transformers). Such mathematical grounding clarifies why models converge or suffer collapse.Combining Existing Theories in Novel WaysPapers such as Moshi (combining text modeling, audio codecs, and hierarchical generative modeling) and Finite Scalar Quantization (FSQ's adaptation of classic scalar quantization to replace vector-quantized representations) show how reusing but reimagining known techniques can yield breakthroughs. Many references (e.g., the structured state-space duality in Transformers are SSMs) underscore how unifying previously separate research lines can reveal powerful algorithmic or theoretical insights.Logical Reasoning and Assumption TestingAcross all papers—particularly in the problem statements of Whisper or Rectified Flow Transformers—the authors present assumptions (e.g., "scaling data leads to zero-shot robustness" or "straight-line noise injection improves sample efficiency") and systematically verify them with thorough empirical results. An ideal researcher similarly grounds new ideas in well-formed, testable hypotheses. 2. Algorithmic Innovation & ImplementationCreative Solutions to Known BottlenecksEach paper puts forth a unique algorithmic contribution—Rectified Flow Transformers redefines standard diffusion paths, FSQ proposes simpler scalar quantizations contrasted with VQ, phi-3 mini relies on curated data and blocksparse attention, and Mamba-2 merges SSM speed with attention concepts.Turning Theory into PracticeWhether it's the direct preference optimization (DPO) for alignment in phi-3 or the residual vector quantization in SoundStream, these works show that bridging design insights with implementable prototypes is essential.Clear Impact Through Prototypes & Open-SourceMany references (Whisper, neural discrete representation learning, Mamba-2) highlight releasing code or pretrained models, enabling the broader community to replicate and build upon new methods. This premise of collaboration fosters faster progress. 3. Data-Driven & Scalable SystemsEmphasis on Large-Scale Data and Efficient PipelinesPapers such as Robust Speech Recognition via Large-Scale Weak Supervision (Whisper) and BASE TTS demonstrate that collecting and processing hundreds of thousands of hours of real-world audio can unlock new capabilities in zero-shot or low-resource domains. Meanwhile, phi-3 Technical Report shows that filtering and curating data at scale (e.g., "data optimal regime") can yield high performance even in smaller models.Strategic Use of Data for Staged TrainingA recurring strategy is to vary sources of data or the order of tasks. Whisper trains on multilingual tasks, BASE TTS uses subsets/stages for pretraining on speech tokens, and phi-3 deploys multiple training phases (web data, then synthetic data). This systematic approach to data underscores how an ideal researcher designs training curricula and data filtering protocols for maximum performance. 4. Hardware & Systems UnderstandingEfficient Implementations at ScaleMany works illustrate how researchers tune architectures for modern accelerators: the In-Datacenter TPU paper exemplifies domain-specific hardware design for dense matrix multiplications, while phi-3 leverages blocksparse attention and custom Triton kernels to run advanced LLMs on resource-limited devices.Real-Time & On-Device ConstraintsSoundStream shows how to compress audio in real time on a smartphone CPU, demonstrating that knowledge of hardware constraints (latency, limited memory) drives design choices. Similarly, Moshi's low-latency streaming TTS and phi-3-mini's phone-based inference highlight that an ideal researcher must adapt algorithms to resource limits while maintaining robustness.Architectural & Optimization DetailsPapers like Mamba-2 in Transformers are SSMs and the In-Datacenter TPU work show how exploiting specialized matrix decomposition, custom memory hierarchies, or quantization approaches can lead to breakthroughs in speed or energy efficiency. 5. Rigorous Experimental DesignControlled Comparisons & AblationsNearly all papers—Whisper, FSQ, Mamba-2, BASE TTS—use systematic ablations to isolate the impact of individual components (e.g., ablation on vector-quantization vs. scalar quantization in FSQ, or size of codebooks in VQ-VAEs). This approach reveals which design decisions truly matter.Multifold Evaluation MetricsFrom MUSHRA listening tests (SoundStream, BASE TTS) to FID in image synthesis (Scaling Rectified Flow Transformers, FSQ) to perplexity or zero-shot generalization in language (phi-3, Scaling Laws for Neural Language Models), the works demonstrate the value of comprehensive, carefully chosen metrics.Stress Tests & Edge CasesWhisper's out-of-distribution speech benchmarks, SoundStream's evaluation on speech + music, or Mamba-2's performance on multi-query associative recall demonstrate the importance of specialized challenge sets. Researchers who craft or adopt rigorous benchmarks and "red-team" their models (as in phi-3 safety alignment) are better prepared to address real-world complexities. SummaryOverall, an ideal researcher in deep learning consistently demonstrates:A solid grounding in theoretical and statistical principlesA talent for proposing and validating new algorithmic solutionsThe capacity to orchestrate data pipelines that scale and reflect real-world diversityAwareness of hardware constraints and system-level trade-offs for efficiencyThorough and transparent experimental practicesThese qualities surface across research on speech (Whisper, BASE TTS), language modeling (Scaling Laws, phi-3), specialized hardware (TPU, Transformers are SSMs), and new representation methods (VQ-VAE, FSQ, SoundStream). By balancing these attributes—rigorous math, innovative algorithms, large-scale data engineering, hardware-savvy optimizations, and reproducible experimentation—researchers can produce impactful, trustworthy advancements in foundational deep learning. Foundational PapersThis job description was generated through analysis of the following papers:Robust Speech Recognition via Large-Scale Weak Supervision (arXiv:2212.04356)Moshi: a speech-text foundation model for real-time dialogue (arXiv:2410.00037)Scaling Rectified Flow Transformers for High-Resolution Image Synthesis (arXiv:2403.03206)Scaling Laws for Neural Language Models (arXiv:2001.08361)BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data (arXiv:2402.08093)In-Datacenter Performance Analysis of a Tensor Processing Unit (arXiv:1704.04760)Neural Discrete Representation Learning (arXiv:1711.00937)SoundStream: An End-to-End Neural Audio Codec (arXiv:2107.03312)Finite Scalar Quantization: VQ-VAE Made Simple (arXiv:2309.15505)Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone (arXiv:2404.14219)Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality (arXiv:2405.21060)Backed by prominent investors including Y Combinator, Madrona, Tiger Global, Wing VC and NVIDIA, Deepgram has raised over $85 million in total funding. If you're looking to work on cutting-edge technology and make a significant impact in the AI industry, we'd love to hear from you!Deepgram is an equal opportunity employer. We want all voices and perspectives represented in our workforce. We are a curious bunch focused on collaboration and doing the right thing. We put our customers first, grow together and move quickly. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, pregnancy, parental status, genetic information, political affiliation, or any other status protected by the laws or regulations in the locations where we operate.We are happy to provide accommodations for applicants who need them.

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Company OverviewDeepgram is the leading voice AI platform for developers building speech-to-text (STT), text-to-speech (TTS) and full speech-to-speech (STS) offerings. 200,000+ developers build with Deepgram’s voice-native foundational models – accessed through APIs or as self-managed software – due to our unmatched accuracy, latency and pricing. Customers include software companies building voice products, co-sell partners working with large enterprises, and enterprises solving internal voice AI use cases. The company ended 2024 cash-flow positive with 400+ enterprise customers, 3.3x annual usage growth across the past 4 years, over 50,000 years of audio processed and over 1 trillion words transcribed. There is no organization in the world that understands voice better than DeepgramThe OpportunityVoice is the most natural modality for human interaction with machines. However, current sequence modeling paradigms based on jointly scaling model and data cannot deliver voice AI capable of universal human interaction. The challenges are rooted in fundamental data problems posed by audio: real-world audio data is scarce and enormously diverse, spanning a vast space of voices, speaking styles, and acoustic conditions. Even if billions of hours of audio were accessible, its inherent high dimensionality creates computational and storage costs that make training and deployment prohibitively expensive at world scale. We believe that entirely new paradigms for audio AI are needed to overcome these challenges and make voice interaction accessible to everyone. The RoleDeepgram is currently looking for an experienced researcher to who has worked extensively with Large Language Models (LLMS) and has a deep understanding of transformer architecture to join our Research Staff. As a Member of the Research Staff, this individual should have extensive experience working on the hard technical aspects of LLMs, such as data curation, distributed large-scale training, optimization of transformer architecture, and Reinforcement Learning (RL) training.The ChallengeWe are seeking researchers who:See "unsolved" problems as opportunities to pioneer entirely new approachesCan identify the one critical experiment that will validate or kill an idea in days, not monthsHave the vision to scale successful proofs-of-concept 100xAre obsessed with using AI to automate and amplify your own impactIf you find yourself energized rather than daunted by these expectations—if you're already thinking about five ideas to try while reading this—you might be the researcher we need. This role demands obsession with the problems, creativity in approach, and relentless drive toward elegant, scalable solutions. The technical challenges are immense, but the potential impact is transformative.What You'll DoBrainstorming and collaborating with other members of the Research Staff to define new LLM research initiativesBroad surveying of literature, evaluating, classifying, and distilling current methodsDesigning and carrying out experimental programs for LLMsDriving transformer (LLM) training jobs successfully on distributed compute infrastructure and deploying new models into productionDocumenting and presenting results and complex technical concepts clearly for a target audienceStaying up to date with the latest advances in deep learning and LLMs, with a particular eye towards their implications and applications within our productsYou'll Love This Role if YouAre passionate about AI and excited about working on state of the art LLM researchHave an interest in producing and applying new science to help us develop and deploy large language modelsEnjoy building from the ground up and love to create new systems.Have strong communication skills and are able to translate complex concepts clearlyAre highly analytical and enjoy delving into detailed analyses when necessary It's Important to Us That You Have3+ years of experience in applied deep learning research, with a solid understanding toward the applications and implications of different neural network types, architectures, and loss mechanismProven experience working with large language models (LLMs) - including experience with data curation, distributed large-scale training, optimization of transformer architecture, and RL LearningStrong experience coding in Python and working with PytorchExperience with various transformer architectures (auto-regressive, sequence-to-sequence.etc)Experience with distributed computing and large-scale data processingPrior experience in conducting experimental programs and using results to optimize modelsIt Would Be Great if You HadDeep understanding of transformers, causal LMs, and their underlying architectureUnderstanding of distributed training and distributed inference schemes for LLMsFamiliarity with RLHF labeling and training pipelinesUp-to-date knowledge of recent LLM techniques and developmentsPublished papers in Deep Learning Research, particularly related to LLMs and deep neural networksBacked by prominent investors including Y Combinator, Madrona, Tiger Global, Wing VC and NVIDIA, Deepgram has raised over $85 million in total funding. If you're looking to work on cutting-edge technology and make a significant impact in the AI industry, we'd love to hear from you!Deepgram is an equal opportunity employer. We want all voices and perspectives represented in our workforce. We are a curious bunch focused on collaboration and doing the right thing. We put our customers first, grow together and move quickly. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, pregnancy, parental status, genetic information, political affiliation, or any other status protected by the laws or regulations in the locations where we operate.We are happy to provide accommodations for applicants who need them.

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About DecagonDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experience. Our AI agents provide intelligent, human-like responses across chat, email, and voice, resolving millions of customer inquiries across every language and at any time.Since coming out of stealth, Decagon has experienced rapid growth. We partner with industry leaders like Hertz, Eventbrite, Duolingo, Oura, Bilt, Curology, and Samsara to redefine customer experience at scale. We've raised over $200M from Bain Capital Ventures, Accel, a16z, BOND Capital, A*, Elad Gil, and notable angels such as the founders of Box, Airtable, Rippling, Okta, Lattice, and Klaviyo.We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values—customers are everything, relentless momentum, winner’s mindset, and stronger together—shape how we work and grow as a team.About the TeamOver the past few years, development of LLMs has evolved at a rapid pace. Building truly successful AI products isn’t just about model quality — it’s about the infrastructure, tooling, and workflows that allow customers to configure, monitor, and improve their agents at scale.The Product Management team owns Decagon’s platform and foundational features: agent building, testing, experimentation, analytics, QA, versioning, integrations, and enterprise controls. We work across every customer segment, partnering closely with engineering, design, and go-to-market to ensure our platform is robust, scalable, and easy to use.As one of our founding PMs, you’ll help define the product foundation that every Decagon customer uses to build and run their AI agents. You’ll own initiatives end-to-end, from discovery and scoping to launch and adoption, shaping the product experience for some of the world’s most influential businesses.About the RoleOn the Product team, you’ll own the roadmap for a major product area and partner with customers and internal teams to deliver features that make Decagon’s platform powerful, flexible, and enterprise-ready. Your work might include:Designing AI-powered features that turn raw conversation data into instant, actionable insights for customers.Building intelligent systems that give enterprises precise control over how their agents learn, adapt, and deploy in production.Creating self-serve configuration experiences that feel effortless — powered by real-time AI guidance and automation.Expanding the platform’s reach by connecting AI agents to live data streams, tools, and APIs that unlock new use cases.You’ll partner closely with engineering, design, sales, agent product managers and our leadership team to ensure the core platform meets the needs of both our largest enterprises and fastest-growing startups.In this role, you willShape the roadmap for core capabilities that power the next generation of AI agents from first concept to launch.Work closely with customers to uncover new ways AI can transform their workflows, unlock automation, and elevate customer experience.Translate breakthrough ideas into clear product specs, then partner with engineering and design to bring them to life.Your background looks something like thisHave 4+ years of relevant experience (e.g., product manager, founder, engineer, researcher etc.)Strong technical acumen — comfortable discussing APIs, data models, and architecture with engineers.Strong communication and relationship-building skills.Proven track record of shipping impactful features in fast-paced environments.Even betterA Computer Science, Engineering, or Math degree or equivalent technical experience.Previous startup or high-growth company experience.Benefits:Medical, dental, and vision benefitsTake what you need vacation policyDaily lunches, dinners and snacks in the office to keep you at your bestCompensation$200K – $285K + Offers Equity

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Join our client's team as a Concierge and AI Trainer, where you'll be instrumental in developing the next generation of AI models tailored to hospitality services. In this role, you'll leverage your expertise in concierge services to train AI systems, providing comprehensive guidance on guest assistance, service delivery, and hospitality standards. Help bridge the gap between expert human service and advanced AI capabilities. Key Responsibilities:Analyze and review AI-generated responses related to concierge services, providing feedback and corrections for accuracy and appropriateness.Apply industry-specific knowledge to create realistic training scenarios, sample dialogues, and task workflows for an AI training platform.Document and communicate best practices for guest service, including special requests, transportation arrangements, and coordination of business or entertainment services.Collaborate with AI development teams to enhance the depth and empathy of AI interactions.Ensure AI responses meet the high standards of written and verbal communication expected from professional concierges.Monitor and assess AI performance across various hospitality tasks, identifying areas for improvement.Stay informed on industry trends and guest expectations to continuously enrich training data. Required Skills and Qualifications:Proven experience as a concierge or similar guest-facing role in hotels, luxury residences, or office buildings.Strong written and verbal communication skills, with a keen focus on detail and guest experience.Ability to define and articulate complex service workflows and hospitality scenarios.Familiarity with arranging transportation, business services, entertainment, and responding to guest requests.Strong organizational and documentation skills for tracking AI feedback and process improvements.Comfortable working independently in a remote environment and collaborating with cross-functional teams.Passion for both technology and delivering exceptional guest service. Preferred Qualifications:Certification from a hospitality or concierge association (e.g., Les Clefs d'Or).Experience in training or mentoring others in hospitality or related fields.Interest or background in AI training or technology development. About RYZ Labs:RYZ Labs is a startup studio founded in 2021 by two lifelong entrepreneurs. The founders of RYZ have worked at some of the world's largest tech companies and some of the most iconic consumer brands. They have lived and worked in Argentina for many years and have decades of experience in Latam. What brought them together was their passion for the early phases of company creation and the idea of attracting the brightest talents in order to build industry-defining companies in a post-pandemic world. Our teams are remote and distributed throughout the US and Latam. They use the latest cutting-edge cloud computing technologies to create scalable and resilient applications. We aim to provide diverse product solutions for different industries and plan to build a large number of startups in the upcoming years. At RYZ, you will find yourself working with autonomy and efficiency, owning every step of your development. We provide an environment of opportunities, learning, growth, expansion, and challenging projects. You will deepen your experience while sharing and learning from a team of great professionals and specialists. Our values and what to expect:- Customer First Mentality - Every decision we make should be made through the lens of the customer.- Bias for Action - urgency is critical, expect that the timeline to get something done is accelerated.- Ownership - Step up if you see an opportunity to help, even if it's not your core responsibility. - Humility and Respect - Be willing to learn, be vulnerable, and treat everyone who interacts with RYZ with respect.- Frugality - being frugal and cost-conscious helps us do more with less- Deliver Impact - get things done most efficiently. - Raise our Standards - always be looking to improve our processes, our team, and our expectations. The status quo is not good enough and never should be.

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Join our client's team as a Clinical Director and AI Trainer, where you'll play a crucial role in advancing healthcare AI systems. Use your leadership and expertise in clinical operations to design AI models that enhance medical and health services management for leading organizations. This unique opportunity lets you shape the future of healthcare technology, working collaboratively and flexibly from any location. Key Responsibilities:Train and guide AI models to accurately represent real-world clinical and administrative decision-making within hospitals, clinics, and healthcare networks.Provide insights and feedback on AI system outputs to ensure alignment with best practices in medical and health services management.Collaborate with cross-functional teams to develop AI training materials and case scenarios based on practical healthcare operations.Provide expert knowledge to help AI trainers simulate the role of Medical and Health Services Managers across diverse healthcare settings.Continuously assess and improve AI content for accuracy, credibility, and relevance to healthcare management applications.Ensure all training and development activities comply with regulatory standards, ethical guidelines, and maintain patient confidentiality.Clearly communicate complex clinical concepts in both written and verbal formats to technical and non-technical audiences. Required Skills and Qualifications:Proven experience as a Clinical Director, Medical and Health Services Manager, or similar leadership role within hospitals, clinics, managed care, or public health agencies.Deep understanding of healthcare operations, medical administration, and industry regulations.Exceptional written and verbal communication skills, with the ability to effectively convey nuanced clinical processes.Strong analytical skills and attention to detail when evaluating systems and processes.Ability to collaborate in a remote, cross-functional environment.Commitment to maintaining the highest standards of integrity, confidentiality, and patient safety.Familiarity with AI or digital health technologies, or a strong willingness to develop these skills. Preferred Qualifications:Experience in training or developing healthcare AI or digital tools.Advanced degree in healthcare administration, public health, or a related field.Proven track record of successful leadership in multidisciplinary, technology-driven projects. About RYZ Labs:RYZ Labs is a startup studio founded in 2021 by two lifelong entrepreneurs. The founders of RYZ have worked at some of the world's largest tech companies and some of the most iconic consumer brands. They have lived and worked in Argentina for many years and have decades of experience in Latam. What brought them together was their passion for the early phases of company creation and the idea of attracting the brightest talents in order to build industry-defining companies in a post-pandemic world. Our teams are remote and distributed throughout the US and Latam. They use the latest cutting-edge cloud computing technologies to create scalable and resilient applications. We aim to provide diverse product solutions for different industries and plan to build a large number of startups in the upcoming years. At RYZ, you will find yourself working with autonomy and efficiency, owning every step of your development. We provide an environment of opportunities, learning, growth, expansion, and challenging projects. You will deepen your experience while sharing and learning from a team of great professionals and specialists. Our values and what to expect:- Customer First Mentality - Every decision we make should be made through the lens of the customer.- Bias for Action - urgency is critical, expect that the timeline to get something done is accelerated.- Ownership - Step up if you see an opportunity to help, even if it's not your core responsibility. - Humility and Respect - Be willing to learn, be vulnerable, and treat everyone who interacts with RYZ with respect.- Frugality - being frugal and cost-conscious helps us do more with less- Deliver Impact - get things done most efficiently. - Raise our Standards - always be looking to improve our processes, our team, and our expectations. The status quo is not good enough and never should be.