Senior Software Engineering Director, Developer Experience
As the Senior Director of Engineering for Developer Experience at Crusoe, you will own and drive the strategy, execution, and culture of the team responsible for how Crusoe's engineers and non-engineers build, ship, and operate software. Responsibilities include defining and executing the long-term vision for Crusoe's internal developer platform, which encompasses shared services, internal APIs, repositories, and self-service infrastructure to enable engineering teams to move quickly and confidently. You will also rapidly develop and productionize AI-powered tools for the entire company, creating and evangelizing best practices for productionizing AI-developed tools and evaluating SaaS purchases. Additionally, you will oversee the design, reliability, and continuous improvement of CI/CD pipelines, build systems, and deployment infrastructure to ensure safe and rapid scaling of engineering teams' shipping processes. Your role will also involve defining and driving organization-wide engineering productivity initiatives by establishing metrics, identifying bottlenecks, and implementing tooling and process improvements that enhance developer experience across Crusoe. People leadership is a key responsibility, including managing and growing a team of engineers and fostering a high-performance culture based on accountability, innovation, and continuous learning. Furthermore, you will collaborate with senior leaders across Engineering, Infrastructure, Security, and Product to align Developer Experience investments with company-wide engineering goals and priorities.
Senior Product Manager – Data & Quality
Partner with frontier AI research labs to design datasets and environments that improve model performance. Lead technical conversations with customer researchers to understand model capabilities, failure modes, data requirements, and success criteria. Probe model behavior through systematic evaluation to uncover weaknesses and identify high-impact data interventions. Design evaluation frameworks, calibration processes, and quality rubrics that establish measurable project success metrics. Develop technical specifications for data projects that balance research rigor with operational feasibility. Serve as thought partner to customer research teams throughout the sales cycle, building trust and credibility. Stay current on frontier AI research, RL environment design, post-training techniques, and evaluation methodologies.
Software Engineer, Internal Tools
Use proprietary software applications to provide input/labels on defined projects. Support and ensure the delivery of high-quality curated data. Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies. Interact with the technical staff to help improve the design of efficient annotation tools. Choose problems from corporate accounting fields that align with your expertise, providing rigorous solutions and model critiques where you can confidently provide detailed solutions and evaluate model responses. Regularly interpret, analyze, and execute tasks based on given instructions.
Machine Learning Operations Engineer
Optimize orchestration processes to ensure efficient deployment and management of AI models. Implement cost-saving strategies to minimize infrastructure expenses while maximizing performance. Upgrade throughput to enhance scalability and responsiveness of AI systems. Collaborate with cross-functional teams to identify bottlenecks and implement solutions to improve workflow efficiency. Ship new features and updates rapidly while maintaining high levels of quality and reliability. Deploy and monitor machine learning models produced by deep learning engineers. Design, deploy, and maintain performant and scalable processes for data acquisition and manipulation to enhance dataset accessibility. Participate actively in the team's software development process, including design reviews, code reviews, and brainstorming sessions. Maintain accurate and updated software development documentation.
Software Engineering Manager, Autonomous
As the Engineering Manager on the Autonomous team, you will lead and scale a high-calibre team of engineers dedicated to defining the future of AI agent development and advancing AI and backend systems. You will oversee the technical roadmap for the Autonomous team, translating architectural complexity into clear product strategies. You will mentor a diverse group of engineers, supporting their professional growth. You will partner closely with Product and Design to ensure the agent-building tools remain intuitive while supporting technical capabilities. You will champion a 'show > tell' culture by ensuring rapid shipping with a high standard for technical stability and user experience. You will clear technical and operational roadblocks to ensure the team operates with high agency and clarity.
AI Tooling Frontend Engineer - Helix Team
Design and build intuitive web interfaces for robot data annotation, datasets visualization, and experiment tracking. Utilize data-driven techniques to optimize interfaces for efficiency and fast iteration cycles. Integrate AI models to automate manual tasks. Work together with AI researchers, robot operators, and annotators to support new user experiences.
Senior Forward-Deployed Engineer, Federal
The Senior Forward-Deployed Engineer, Federal at Deepgram is responsible for owning technical delivery across federal deployments from initial prototype to stable production. They embed deeply with federal customers to design and build mission-critical applications using Deepgram's Voice AI models, lead technical discovery and solution design for federal prospects and customers, and prototype and build full-stack integrations with technologies such as Python, JavaScript, or Rust. They enable successful deployments by delivering observable systems spanning infrastructure through applications and proactively guide federal stakeholders on platform operational value, including performance optimization and deployment strategies. Responsibilities include scoping work, sequencing delivery, removing blockers, managing relationships with customer leadership and technical stakeholders, contributing to code when necessary, codifying working patterns into reusable tools and playbooks, sharing field feedback with Product and Engineering, serving as an escalation point for technical issues, and analyzing deployment patterns to inform product and go-to-market strategies. The role involves significant collaboration internally and externally, including technical engagements pre-sales, building reusable solutions, and contributing to Applied Engineering strategy.
Senior Engineering Manager, Handshake AI
The Senior Engineering Manager leads a core product and platform engineering team building systems that integrate human expertise into AI development workflows. This team owns critical infrastructure connecting talent networks, data operations, and research needs into scalable, reliable, and high-quality platforms. The manager leads, hires, and develops a high-performing engineering team, owns the roadmap and execution in partnership with Product, Research, and Operations, drives architecture and technical strategy for scalable and extensible systems, builds modular platforms for new domains, workflows, and partners, raises engineering quality across reliability, observability, performance, and data integrity, and fosters a culture of ownership, velocity, and strong engineering fundamentals in a fast-moving environment.
Lead AI/ML Engineer
Lead the design and implementation of scalable ML/AI systems focused on large language models, vector databases, and retrieval-based architectures. Integrate and apply foundation models from providers like OpenAI, AWS Bedrock, and Anthropic for prototyping and production use cases. Adapt, evaluate, and optimize large language models for domain-specific enterprise applications. Build and maintain infrastructure for AI model experimentation, deployment, and monitoring in production. Improve model performance and inference workflows addressing latency, cost, and reliability. Provide technical leadership by mentoring engineers and promoting best ML engineering practices. Partner with product and cross-functional stakeholders to translate requirements into scalable ML solutions. Contribute to the evolution of internal standards for AI experimentation, evaluation, and deployment. Lead the design and delivery of end-to-end voice AI solutions combining large language models with speech technologies including speech-to-text, text-to-speech, and real-time streaming audio pipelines, architecting low-latency, highly reliable conversational voice systems and guiding a team through ambiguity toward production excellence. Understand and apply constraints of voice experiences such as latency, turn-taking, interruption handling, streaming inference, and audio quality to create scalable, enterprise-grade systems.
Senior Product Designer, Mobile
Own the observability and lifecycle management of AI features across the organization. Build tools and infrastructure to enable teams to develop, monitor, and optimize LLM-powered features. Design and implement closed-loop evaluation pipelines that automatically validate prompt changes. Develop comprehensive metrics and dashboards to track LLM usage including cost per feature, token patterns, and latency. Create systems that tie user feedback to specific prompts and LLM calls. Establish best practices and processes for the full lifecycle of prompts including development, testing, deployment, and monitoring. Collaborate with engineering teams to ensure they have the tools and visibility needed to build high-quality AI features.
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