Top AI Engineer Jobs Openings in 2025

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Salary Range: $130,000-$180,000/year (Range shown is for U.S.-based employees in San Francisco, CA. Compensation outside the U.S. is adjusted fairly based on your country's cost of living.)Equity Range: Up to 0.10%Location: San Francisco, CA (Hybrid) OR RemoteJob Type: Full-Time (SF) OR Contract (Remote)Experience: 2+ yearsAbout FirecrawlFirecrawl is the easiest way to extract data from the web. Developers use us to reliably convert URLs into LLM-ready markdown or structured data with a single API call. In just a year, we've hit millions in ARR and 70k+ GitHub stars by building the fastest way for developers to get LLM-ready data.We're a small, fast-moving, technical team building essential infrastructure for the AI era. We value autonomy, clarity, and shipping fast.About the RoleWe're looking for an AI Engineer to own the technical side of our partnerships motion. Your mission: make Firecrawl the default web data API that AI agents and tools reach for. You'll work directly with emerging AI-native companies - writing prompts, building evals, and ensuring Firecrawl integrations just work.What You'll DoCraft and iterate on prompts that help AI agents reliably choose and use Firecrawl for web data tasksBuild evaluation frameworks to test prompts across different models, use cases, and edge cases - then iterate relentlessly based on resultsBe the technical partner contact in Slack channels, helping partners implement Firecrawl into their products and troubleshoot issues in real-timeTest obsessively - new models drop, agent architectures evolve, and you're on top of how Firecrawl performs across all of themCreate integration guides and templates that make it dead simple for partners to ship Firecrawl-powered featuresIdentify new partnership opportunities by understanding how AI tools are using web data and where Firecrawl fitsCollaborate with Product and Engineering to surface partner feedback and shape the roadmapWho You Are2+ years working with LLMs - you've written production prompts, understand model quirks, and know what makes agents tickYou ship code. Python, TypeScript, whatever - you can build evals, write scripts, and prototype integrations quicklyYou're a clear communicator who can help non-technical partners implement technical solutionsYou thrive in ambiguity - partnerships are messy, timelines shift, and you figure it outYou're responsive and reliable - when a partner pings in Slack, you're on itBonus: You've worked at an AI-native company or have experience with agent frameworks (LangChain, CrewAI, OpenAI Agents SDK, etc.)Bonus: You've done developer relations, solutions engineering, or technical partnerships beforeBenefits & PerksAvailable to all employeesSalary that makes sense - $130,000-180,000/year OTE (U.S.-based), based on impact, not tenureOwn a piece - Up to 0.10% equity in what you're helping buildGenerous PTO - 15 days mandatory, anything after 24 days, just ask (holidays excluded); take the time you need to rechargeParental leave - 12 weeks fully paid, for moms and dadsWellness stipend - $100/month for the gym, therapy, massages, or whatever keeps you humanLearning & Development - Expense up to $150/year toward anything that helps you grow professionallyTeam offsites - A change of scenery, minus the trust fallsSabbatical - 3 paid months off after 4 years, do something fun and newAvailable to US-based full-time employeesFull coverage, no red tape - Medical, dental, and vision (100% for employees, 50% for spouse/kids) - no weird loopholes, just care that worksLife & Disability insurance - Employer-paid short-term disability, long-term disability, and life insurance - coverage for life's curveballsSupplemental options - Optional accident, critical illness, hospital indemnity, and voluntary life insurance for extra peace of mindDoctegrity telehealth - Talk to a doctor from your couch401(k) plan - Retirement might be a ways off, but future-you will thank youPre-tax benefits - Access to FSAs and commuter benefits (US-only) to help your wallet out a bitPet insurance - Because fur babies are family tooAvailable to SF-based employeesSF HQ perks - Snacks, drinks, team lunches, intense ping pong, and peak startup energyE-Bike transportation - A loaner electric bike to get you around the city, on usInterview ProcessApplication ReviewIntro Chat (~25 min)Technical Deep Dive (~45 min)Paid Work Trial (1-2 weeks)DecisionIf you're an AI engineer who lives in Slack, obsesses over prompt quality, and wants to make Firecrawl the infrastructure layer for AI agents everywhere - let's talk.

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Who are we?Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.Join us on our mission and shape the future!Why this role?We’re a fast-growing startup building production-grade AI agents for enterprise customers at scale. We’re looking for Applied AI Engineers who can own the design, build, and deployment of agentic workflows powered by Large Language Models (LLMs)—from early prototypes to production-grade AI agents, to deliver concrete business value in enterprise workflows.In this role, you’ll work closely with customers on real-world business problems, often building first-of-their-kind agent workflows that integrate LLMs with tools, APIs, and data sources. While our pace is startup-fast, the bar is enterprise-high: agents must be reliable, observable, safe, and auditable from day one.You’ll collaborate closely with customers, product, and platform teams, and help shape how agentic systems are built, evaluated, and deployed at scale.What You’ll DoWork with enterprise customers and internal teams to turn business workflows into scalable, production-ready agentic AI systems.Design and build LLM-powered agents that reason, plan, and act across tools and data sources with enterprise-grade reliability.Balance rapid iteration with enterprise requirements, evolving prototypes into stable, reusable solutions.Define and apply evaluation and quality standards to measure success, failures, and regressions.Debug real-world agent behavior and systematically improve prompts, workflows, tools, and guardrails.Contribute to shared frameworks and patterns that enable consistent delivery across customers.Required Skills & ExperienceBachelor’s degree in Computer Science or a related technical field.Strong programming skills in Python and/or JavaScript/TypeScript.3+ years of experience building and shipping production software; 2+ years working with LLMs or AI APIs.Hands-on experience with modern LLMs (e.g., GPT, Claude, Gemini), vector databases, and agent/orchestration frameworks (e.g., LangChain, LangGraph, LlamaIndex, or custom solutions).Practical experience with RAG, agent workflows, evaluation, and performance optimization.Strong agent design skills, including prompt engineering, tool use, multi-step agent workflows (e.g. ReAct), and failure handling.Ability to reason about and balance trade-offs between customization and reuse, as well as autonomy, control, cost, latency, and risk.Strong communication skills and experience leading technical discussions with customers or partners.Nice-to-HaveExperience working in a fast-moving startup environment.Prior work delivering AI or automation solutions to enterprise customers.Familiarity with human-in-the-loop workflows, fine-tuning, or LLM evaluation techniques.Experience with cloud deployment and production operations for AI systems.Background in applied ML, NLP, or decision systems.Additional RequirementsStrong written and verbal communication skills.Ability and interest to travel up to 25%, flexible.Why Join UsBuild production-grade AI agents used in real enterprise workflows.Operate at scale while retaining end-to-end ownership.Work on hard problems in agent design, evaluation, and reliability.Shape shared platforms and standards, not just individual features.Move fast with a high bar for quality, safety, and reliability.If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.Full-Time Employees at Cohere enjoy these Perks:🤝 An open and inclusive culture and work environment 🧑‍💻 Work closely with a team on the cutting edge of AI research 🍽 Weekly lunch stipend, in-office lunches & snacks🦷 Full health and dental benefits, including a separate budget to take care of your mental health 🐣 100% Parental Leave top-up for up to 6 months🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend✈️ 6 weeks of vacation (30 working days!)

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Warp: We're Building the Platform for Agentic Development Warp began with the vision of reimagining one of the fundamental dev tools—the terminal—to make it more usable and powerful for all developers. As AI has advanced, Warp has evolved beyond its terminal roots into the platform for Agentic Development: a workbench for dispatching agents to code, deploy, and debug production software. With over 700k active developers and revenue that has grown over 20x this year so far, Warp is now one of the fastest growing startups in the exploding AI development space. We believe that soon developers will be “tech leads” for groups of agents; rather than opening a code editor to write code or a terminal to write commands, they will open Warp and prompt their computer to build features, fix bugs, and diagnose production issues. With its starting point as a reimagined command line, Warp is well-positioned to support agent-first workflows: It sits at the lowest level in the dev stack, has access to all of a developer’s context, and is set up for multitasking and long-running processes. In addition, Warp has state-of-the-art code editing features and built-in team knowledge sharing. It’s the right interface for the agentic future. Our mission has remained the same even as AI has advanced: to empower developers to ship better software more quickly, freeing them to focus on the creative and rewarding aspects of their work. For more information on our team and culture, we highly recommend reading our How We Work.Why this role? Warp is fundamentally changing how developers interact with technology, moving from coding "by hand" to working "by prompt." We're hiring an Applied AI Engineer to accelerate this transformation.  You’ll be instrumental in developing innovative predictive AI features leveraging our unique user-generated content and team data. This applied AI Engineer role emphasizes product development and implementation, distinguishing it from a purely research-oriented position. You will be directly reporting to John Rector, our Head of Engineering. Your work will supercharge our natural language understanding, enhance predictive accuracy for commands, and build personalized, specialized AI agents. By continuously refining our AI-driven suggestions and agent interactions, you'll empower hundreds of thousands of developers globally to ship better software faster, significantly impacting Warp's core product. As our first Applied AI Engineer, you will… Design, build, and deploy predictive AI features, including natural language detection, autosuggestions, and intelligent prompt recommendations. Leverage Warp’s extensive user-generated content and team data to continuously refine AI prediction and personalization. Drive substantial improvements in code generation quality, including code completions, diff applications, and SWEbench performance. Implement and iterate specialized agents tailored for specific developer workflows and use cases. Optimize AI models through fine-tuning, advanced prompt engineering, and robust, data-driven feedback loops. Improve context retrieval systems, enabling Warp agents to retain and utilize memory effectively. Collaborate closely with product and engineering teams, rapidly shipping iterative improvements into production. Continuously elevate the user experience by refining interactions between developers and Warp AI. You may be a good fit if… You have at least 5 years of experience applying AI/ML research to build and ship user-facing, production-grade products.  You possess a strong software engineering background You have experience in fine-tuning and deploying large language models and predictive systems. You're adept at prompt engineering and able to craft and iterate on prompts to optimize AI outputs and agent performance. You’re comfortable building scalable data-driven feedback loops to measure and improve model accuracy and user satisfaction. You thrive in a fast-paced environment, prioritizing shipping high-quality improvements over pure theoretical research. Bonus points if you’ve previously built or significantly enhanced developer-facing AI products, particularly those involving command-line or coding assistance. At Warp, we are dedicated to building a diverse, inclusive, and authentic workplace. If you’re excited about this role but your past experience doesn’t align perfectly with every qualification, we encourage you to apply anyway! Most of us are learning new skills for the first time (like our engineers learning to program Warp in Rust). You might be just the right candidate for this or other roles. Feeling playful? Try our optional hiring challenge and submit your answers with your application: Warp Hiring Challenge Salary Transparency Total compensation at Warp consists of two parts: 1) a competitive base salary, and 2) meaningful equity. When we find the right person, we try to put our best foot forward with an offer that excites you. The budgeted compensation range for this role is targeted at $220,000 – $275,000. Final total compensation depends on experience and expertise. In addition to salary, all employees receive further compensation in the form of equity in the company. This is a meaningful stock option grant with a four-year vesting period and one-year cliff. Your equity is where most of the significant upside potential is. Comparing startup equity is always a bit tricky, so we’re happy to walk you through different valuation scenarios at the offer stage in order to help paint a clearer picture of the upside. Final total compensation is determined by multiple factors including your experience and expertise and may vary from the amounts listed above. What We Offer Competitive Salary & Meaningful Equity – we will stretch to get the right talent on board Full Medical, Dental, and Vision Benefits for employees (80% coverage for dependents) Flexible remote-first culture, with optional office spaces in NYC and SF for folks who want to work together IRL  Pre-tax FSA Health Savings Plan Pre-tax Commuter Benefit 20-days of Paid Time Off Unlimited Sick Time Off 12 US Holidays 16 weeks of paid Parental Leave for both birthing and non-birthing parents Twice-a-year company retreats Monthly gym and internet stipend Guideline 401(k) Complimentary OneMedical membership Individuals seeking employment at Warp are considered without regards to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.About Warp We are a company run by product-first builders, building a core product for all developers. We are committed to understanding our users deeply. We will ultimately build the best product and business if that team includes developers and designers from a wide range of backgrounds. The early team comes from Google, Dropbox, Gem, LinkedIn, and Facebook. We are looking for passionate individuals to join us and help bring Warp to the world. We value honesty, humility, and pragmatism, and our core product principle is focusing on the user. If you’re interested in learning more about our company values and the culture of our engineering team, please take a look at our internal 'How We Work' guide. We’re very fortunate to be backed by a great group of venture capital firms. In August 2023, we announced a $50M Series B funding round ($73M total raised), led by Sequoia Capital. Our other investors include Google Ventures, Neo, and Box Group. We are also backed by a network of passionate angels, including Dylan Field (Co-Founder and CEO, Figma), Elad Gil (early investor in Airbnb, Pinterest, Stripe, and Square), Jeff Weiner (Executive Chairman and Ex-CEO, LinkedIn), Marc Benioff (Founder and CEO, Salesforce), and Sam Altman (Co-Founder & CEO, OpenAI). The Product Here's our latest demo showing some of our current features…

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI. What we doThe Mindrift platform, launched and powered by Toloka, connects domain experts with cutting-edge AI projects from innovative tech clients. Our mission is to unlock the potential of GenAI by tapping into real-world expertise from across the globe. Who we're looking forCalling all security researchers, engineers, and penetration testers with a strong foundation in problem-solving, offensive security, and AI-related risk assessment.If you thrive on digging into complex systems, uncovering hidden vulnerabilities, and thinking creatively under constraints, join us! We’re looking for someone who can bring a hands-on approach to technical challenges, whether breaking into systems to expose weaknesses or building secure tools and processes. We value contributors with a passion for continuous learning, experimentation, and adaptability. About the projectWe’re on the hunt for hands-on Python engineers for a new project focused on developing Model Context Protocol (MCP) servers and internal tools for running and evaluating agent behavior. You’ll implement base methods for agent action verification, integrate with internal and client infrastructures, and help fill tooling gaps across the team. What you’ll be doing:Developing and maintaining MCP-compatible evaluation serversImplementing logic to check agent actions against scenario definitionsCreating or extending tools that writers and QAs use to test agentsWorking closely with infrastructure engineers to ensure compatibilityOccasionally helping with test writing or debug sessions when neededAlthough we’re only looking for experts for this current project, contributors with consistent high-quality submissions may receive an invitation for ongoing collaboration across future projects. How to get started:Apply to this post, qualify, and get the chance to contribute to a project aligned with your skills, on your own schedule. Shape the future of AI while building tools that benefit everyone.RequirementsThe ideal contributor will have:4+ years of Python development experience, ideally in backend or toolsSolid experience building APIs, testing frameworks, or protocol-based interfacesUnderstanding of Docker, Linux CLI, and HTTP-based communicationAbility to integrate new tools into existing infrastructuresFamiliarity with how LLM agents are prompted, executed, and evaluatedClear documentation and communication skills - you’ll work with QA and writersWe also value applicants who have:Experience with Model Context Protocol (MCP) or similar structured agent-server interfacesKnowledge of FastAPI or similar async web frameworksExperience working with LLM logs, scoring functions, or sandbox environmentsAbility to support dev environments (devcontainers, CI configs, linters)JS experienceBenefitsGet paid for your expertise, with rates that can go up to $80/hour depending on your skills, experience, and project needs.Take part in a flexible, remote, freelance project that fits around your primary professional or academic commitments.Participate in an advanced AI project and gain valuable experience to enhance your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI. What we doThe Mindrift platform, launched and powered by Toloka, connects domain experts with cutting-edge AI projects from innovative tech clients. Our mission is to unlock the potential of GenAI by tapping into real-world expertise from across the globe. Who we're looking forCalling all security researchers, engineers, and penetration testers with a strong foundation in problem-solving, offensive security, and AI-related risk assessment.If you thrive on digging into complex systems, uncovering hidden vulnerabilities, and thinking creatively under constraints, join us! We’re looking for someone who can bring a hands-on approach to technical challenges, whether breaking into systems to expose weaknesses or building secure tools and processes. We value contributors with a passion for continuous learning, experimentation, and adaptability. About the projectWe’re on the hunt for hands-on Python engineers for a new project focused on developing Model Context Protocol (MCP) servers and internal tools for running and evaluating agent behavior. You’ll implement base methods for agent action verification, integrate with internal and client infrastructures, and help fill tooling gaps across the team. What you’ll be doing:Developing and maintaining MCP-compatible evaluation serversImplementing logic to check agent actions against scenario definitionsCreating or extending tools that writers and QAs use to test agentsWorking closely with infrastructure engineers to ensure compatibilityOccasionally helping with test writing or debug sessions when neededAlthough we’re only looking for experts for this current project, contributors with consistent high-quality submissions may receive an invitation for ongoing collaboration across future projects. How to get started:Apply to this post, qualify, and get the chance to contribute to a project aligned with your skills, on your own schedule. Shape the future of AI while building tools that benefit everyone.RequirementsThe ideal contributor will have:4+ years of Python development experience, ideally in backend or toolsSolid experience building APIs, testing frameworks, or protocol-based interfacesUnderstanding of Docker, Linux CLI, and HTTP-based communicationAbility to integrate new tools into existing infrastructuresFamiliarity with how LLM agents are prompted, executed, and evaluatedClear documentation and communication skills - you’ll work with QA and writersWe also value applicants who have:Experience with Model Context Protocol (MCP) or similar structured agent-server interfacesKnowledge of FastAPI or similar async web frameworksExperience working with LLM logs, scoring functions, or sandbox environmentsAbility to support dev environments (devcontainers, CI configs, linters)JS experienceBenefitsGet paid for your expertise, with rates that can go up to $12/hour depending on your skills, experience, and project needs.Take part in a flexible, remote, freelance project that fits around your primary professional or academic commitments.Participate in an advanced AI project and gain valuable experience to enhance your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English.At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI. What we doThe Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleWe’re looking for someone who can design realistic and structured evaluation scenarios for LLM-based agents. You’ll create test cases that simulate human-performed tasks and define gold-standard behavior to compare agent actions against. You’ll work to ensure each scenario is clearly defined, well-scored, and easy to execute and reuse. You’ll need a sharp analytical mindset, attention to detail, and an interest in how AI agents make decisions. Although every project is unique, you might typically:Create structured test cases that simulate complex human workflows.Define gold-standard behavior and scoring logic to evaluate agent actions. Analyze agent logs, failure modes, and decision paths.Work with code repositories and test frameworks to validate your scenarios.Iterate on prompts, instructions, and test cases to improve clarity and difficulty.Ensure that scenarios are production-ready, easy to run, and reusable.How to get startedSimply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone.RequirementsBachelor's and/or Master’s Degree in Computer Science, Software Engineering, Data Science / Data Analytics, Artificial Intelligence / Machine Learning, Computational Linguistics / Natural Language Processing (NLP), Information Systems or other related fields. Background in QA, software testing, data analysis, or NLP annotation.Good understanding of test design principles (e.g., reproducibility, coverage, edge cases).Strong written communication skills in English.Comfortable with structured formats like JSON/YAML for scenario description.Can define expected agent behaviors (gold paths) and scoring logic.Basic experience with Python and JS.Curious and open to working with AI-generated content, agent logs, and prompt-based behavior.Nice to HaveExperience in writing manual or automated test cases.Familiarity with LLM capabilities and typical failure modes.Understanding of scoring metrics (precision, recall, coverage, reward functions).BenefitsContribute on your own schedule, from anywhere in the world. This opportunity allows you to:Get paid for your expertise, with rates that can go up to $50/hour depending on your skills, experience, and project needs.Take part in a flexible, remote, freelance project that fits around your primary professional or academic commitments.Participate in an advanced AI project and gain valuable experience to enhance your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English.At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI. What we doThe Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleWe’re looking for someone who can design realistic and structured evaluation scenarios for LLM-based agents. You’ll create test cases that simulate human-performed tasks and define gold-standard behavior to compare agent actions against. You’ll work to ensure each scenario is clearly defined, well-scored, and easy to execute and reuse. You’ll need a sharp analytical mindset, attention to detail, and an interest in how AI agents make decisions. Although every project is unique, you might typically:Create structured test cases that simulate complex human workflows.Define gold-standard behavior and scoring logic to evaluate agent actions. Analyze agent logs, failure modes, and decision paths.Work with code repositories and test frameworks to validate your scenarios.Iterate on prompts, instructions, and test cases to improve clarity and difficulty.Ensure that scenarios are production-ready, easy to run, and reusable.How to get startedSimply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone.RequirementsBachelor's and/or Master’s Degree in Computer Science, Software Engineering, Data Science / Data Analytics, Artificial Intelligence / Machine Learning, Computational Linguistics / Natural Language Processing (NLP), Information Systems or other related fields. Background in QA, software testing, data analysis, or NLP annotation.Good understanding of test design principles (e.g., reproducibility, coverage, edge cases).Strong written communication skills in English.Comfortable with structured formats like JSON/YAML for scenario description.Can define expected agent behaviors (gold paths) and scoring logic.Basic experience with Python and JS.Curious and open to working with AI-generated content, agent logs, and prompt-based behavior.Nice to HaveExperience in writing manual or automated test cases.Familiarity with LLM capabilities and typical failure modes.Understanding of scoring metrics (precision, recall, coverage, reward functions).BenefitsContribute on your own schedule, from anywhere in the world. This opportunity allows you to:Get paid for your expertise, with rates that can go up to $30/hour depending on your skills, experience, and project needs.Take part in a flexible, remote, freelance project that fits around your primary professional or academic commitments.Participate in an advanced AI project and gain valuable experience to enhance your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English.At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI. What we doThe Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleWe’re looking for someone who can design realistic and structured evaluation scenarios for LLM-based agents. You’ll create test cases that simulate human-performed tasks and define gold-standard behavior to compare agent actions against. You’ll work to ensure each scenario is clearly defined, well-scored, and easy to execute and reuse. You’ll need a sharp analytical mindset, attention to detail, and an interest in how AI agents make decisions. Although every project is unique, you might typically:Create structured test cases that simulate complex human workflows.Define gold-standard behavior and scoring logic to evaluate agent actions. Analyze agent logs, failure modes, and decision paths.Work with code repositories and test frameworks to validate your scenarios.Iterate on prompts, instructions, and test cases to improve clarity and difficulty.Ensure that scenarios are production-ready, easy to run, and reusable.How to get startedSimply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone.RequirementsBachelor's and/or Master’s Degree in Computer Science, Software Engineering, Data Science / Data Analytics, Artificial Intelligence / Machine Learning, Computational Linguistics / Natural Language Processing (NLP), Information Systems or other related fields. Background in QA, software testing, data analysis, or NLP annotation.Good understanding of test design principles (e.g., reproducibility, coverage, edge cases).Strong written communication skills in English.Comfortable with structured formats like JSON/YAML for scenario description.Can define expected agent behaviors (gold paths) and scoring logic.Basic experience with Python and JS.Curious and open to working with AI-generated content, agent logs, and prompt-based behavior.Nice to HaveExperience in writing manual or automated test cases.Familiarity with LLM capabilities and typical failure modes.Understanding of scoring metrics (precision, recall, coverage, reward functions).BenefitsContribute on your own schedule, from anywhere in the world. This opportunity allows you to:Get paid for your expertise, with rates that can go up to $45/hour depending on your skills, experience, and project needs.Take part in a flexible, remote, freelance project that fits around your primary professional or academic commitments.Participate in an advanced AI project and gain valuable experience to enhance your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI. What we doThe Mindrift platform, launched and powered by Toloka, connects domain experts with cutting-edge AI projects from innovative tech clients. Our mission is to unlock the potential of GenAI by tapping into real-world expertise from across the globe. Who we're looking forCalling all security researchers, engineers, and penetration testers with a strong foundation in problem-solving, offensive security, and AI-related risk assessment.If you thrive on digging into complex systems, uncovering hidden vulnerabilities, and thinking creatively under constraints, join us! We’re looking for someone who can bring a hands-on approach to technical challenges, whether breaking into systems to expose weaknesses or building secure tools and processes. We value contributors with a passion for continuous learning, experimentation, and adaptability. About the projectWe’re on the hunt for hands-on Python engineers for a new project focused on developing Model Context Protocol (MCP) servers and internal tools for running and evaluating agent behavior. You’ll implement base methods for agent action verification, integrate with internal and client infrastructures, and help fill tooling gaps across the team. What you’ll be doing:Developing and maintaining MCP-compatible evaluation serversImplementing logic to check agent actions against scenario definitionsCreating or extending tools that writers and QAs use to test agentsWorking closely with infrastructure engineers to ensure compatibilityOccasionally helping with test writing or debug sessions when neededAlthough we’re only looking for experts for this current project, contributors with consistent high-quality submissions may receive an invitation for ongoing collaboration across future projects. How to get started:Apply to this post, qualify, and get the chance to contribute to a project aligned with your skills, on your own schedule. Shape the future of AI while building tools that benefit everyone.RequirementsThe ideal contributor will have:4+ years of Python development experience, ideally in backend or toolsSolid experience building APIs, testing frameworks, or protocol-based interfacesUnderstanding of Docker, Linux CLI, and HTTP-based communicationAbility to integrate new tools into existing infrastructuresFamiliarity with how LLM agents are prompted, executed, and evaluatedClear documentation and communication skills - you’ll work with QA and writersWe also value applicants who have:Experience with Model Context Protocol (MCP) or similar structured agent-server interfacesKnowledge of FastAPI or similar async web frameworksExperience working with LLM logs, scoring functions, or sandbox environmentsAbility to support dev environments (devcontainers, CI configs, linters)JS experienceBenefitsGet paid for your expertise, with rates that can go up to $30/hour depending on your skills, experience, and project needs.Take part in a flexible, remote, freelance project that fits around your primary professional or academic commitments.Participate in an advanced AI project and gain valuable experience to enhance your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI. What we doThe Mindrift platform, launched and powered by Toloka, connects domain experts with cutting-edge AI projects from innovative tech clients. Our mission is to unlock the potential of GenAI by tapping into real-world expertise from across the globe. Who we're looking forCalling all security researchers, engineers, and penetration testers with a strong foundation in problem-solving, offensive security, and AI-related risk assessment.If you thrive on digging into complex systems, uncovering hidden vulnerabilities, and thinking creatively under constraints, join us! We’re looking for someone who can bring a hands-on approach to technical challenges, whether breaking into systems to expose weaknesses or building secure tools and processes. We value contributors with a passion for continuous learning, experimentation, and adaptability. About the projectWe’re on the hunt for hands-on Python engineers for a new project focused on developing Model Context Protocol (MCP) servers and internal tools for running and evaluating agent behavior. You’ll implement base methods for agent action verification, integrate with internal and client infrastructures, and help fill tooling gaps across the team. What you’ll be doing:Developing and maintaining MCP-compatible evaluation serversImplementing logic to check agent actions against scenario definitionsCreating or extending tools that writers and QAs use to test agentsWorking closely with infrastructure engineers to ensure compatibilityOccasionally helping with test writing or debug sessions when neededAlthough we’re only looking for experts for this current project, contributors with consistent high-quality submissions may receive an invitation for ongoing collaboration across future projects. How to get started:Apply to this post, qualify, and get the chance to contribute to a project aligned with your skills, on your own schedule. Shape the future of AI while building tools that benefit everyone.RequirementsThe ideal contributor will have:4+ years of Python development experience, ideally in backend or toolsSolid experience building APIs, testing frameworks, or protocol-based interfacesUnderstanding of Docker, Linux CLI, and HTTP-based communicationAbility to integrate new tools into existing infrastructuresFamiliarity with how LLM agents are prompted, executed, and evaluatedClear documentation and communication skills - you’ll work with QA and writersWe also value applicants who have:Experience with Model Context Protocol (MCP) or similar structured agent-server interfacesKnowledge of FastAPI or similar async web frameworksExperience working with LLM logs, scoring functions, or sandbox environmentsAbility to support dev environments (devcontainers, CI configs, linters)JS experienceBenefitsGet paid for your expertise, with rates that can go up to $80/hour depending on your skills, experience, and project needs.Take part in a flexible, remote, freelance project that fits around your primary professional or academic commitments.Participate in an advanced AI project and gain valuable experience to enhance your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI. What we doThe Mindrift platform, launched and powered by Toloka, connects domain experts with cutting-edge AI projects from innovative tech clients. Our mission is to unlock the potential of GenAI by tapping into real-world expertise from across the globe. Who we're looking forCalling all security researchers, engineers, and penetration testers with a strong foundation in problem-solving, offensive security, and AI-related risk assessment.If you thrive on digging into complex systems, uncovering hidden vulnerabilities, and thinking creatively under constraints, join us! We’re looking for someone who can bring a hands-on approach to technical challenges, whether breaking into systems to expose weaknesses or building secure tools and processes. We value contributors with a passion for continuous learning, experimentation, and adaptability. About the projectWe’re on the hunt for hands-on Python engineers for a new project focused on developing Model Context Protocol (MCP) servers and internal tools for running and evaluating agent behavior. You’ll implement base methods for agent action verification, integrate with internal and client infrastructures, and help fill tooling gaps across the team. What you’ll be doing:Developing and maintaining MCP-compatible evaluation serversImplementing logic to check agent actions against scenario definitionsCreating or extending tools that writers and QAs use to test agentsWorking closely with infrastructure engineers to ensure compatibilityOccasionally helping with test writing or debug sessions when neededAlthough we’re only looking for experts for this current project, contributors with consistent high-quality submissions may receive an invitation for ongoing collaboration across future projects. How to get started:Apply to this post, qualify, and get the chance to contribute to a project aligned with your skills, on your own schedule. Shape the future of AI while building tools that benefit everyone.RequirementsThe ideal contributor will have:4+ years of Python development experience, ideally in backend or toolsSolid experience building APIs, testing frameworks, or protocol-based interfacesUnderstanding of Docker, Linux CLI, and HTTP-based communicationAbility to integrate new tools into existing infrastructuresFamiliarity with how LLM agents are prompted, executed, and evaluatedClear documentation and communication skills - you’ll work with QA and writersWe also value applicants who have:Experience with Model Context Protocol (MCP) or similar structured agent-server interfacesKnowledge of FastAPI or similar async web frameworksExperience working with LLM logs, scoring functions, or sandbox environmentsAbility to support dev environments (devcontainers, CI configs, linters)JS experienceBenefitsGet paid for your expertise, with rates that can go up to $80/hour depending on your skills, experience, and project needs.Take part in a flexible, remote, freelance project that fits around your primary professional or academic commitments.Participate in an advanced AI project and gain valuable experience to enhance your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI. What we doThe Mindrift platform, launched and powered by Toloka, connects domain experts with cutting-edge AI projects from innovative tech clients. Our mission is to unlock the potential of GenAI by tapping into real-world expertise from across the globe. Who we're looking forCalling all security researchers, engineers, and penetration testers with a strong foundation in problem-solving, offensive security, and AI-related risk assessment.If you thrive on digging into complex systems, uncovering hidden vulnerabilities, and thinking creatively under constraints, join us! We’re looking for someone who can bring a hands-on approach to technical challenges, whether breaking into systems to expose weaknesses or building secure tools and processes. We value contributors with a passion for continuous learning, experimentation, and adaptability. About the projectWe’re on the hunt for hands-on Python engineers for a new project focused on developing Model Context Protocol (MCP) servers and internal tools for running and evaluating agent behavior. You’ll implement base methods for agent action verification, integrate with internal and client infrastructures, and help fill tooling gaps across the team. What you’ll be doing:Developing and maintaining MCP-compatible evaluation serversImplementing logic to check agent actions against scenario definitionsCreating or extending tools that writers and QAs use to test agentsWorking closely with infrastructure engineers to ensure compatibilityOccasionally helping with test writing or debug sessions when neededAlthough we’re only looking for experts for this current project, contributors with consistent high-quality submissions may receive an invitation for ongoing collaboration across future projects. How to get started:Apply to this post, qualify, and get the chance to contribute to a project aligned with your skills, on your own schedule. Shape the future of AI while building tools that benefit everyone.RequirementsThe ideal contributor will have:4+ years of Python development experience, ideally in backend or toolsSolid experience building APIs, testing frameworks, or protocol-based interfacesUnderstanding of Docker, Linux CLI, and HTTP-based communicationAbility to integrate new tools into existing infrastructuresFamiliarity with how LLM agents are prompted, executed, and evaluatedClear documentation and communication skills - you’ll work with QA and writersWe also value applicants who have:Experience with Model Context Protocol (MCP) or similar structured agent-server interfacesKnowledge of FastAPI or similar async web frameworksExperience working with LLM logs, scoring functions, or sandbox environmentsAbility to support dev environments (devcontainers, CI configs, linters)JS experienceBenefitsGet paid for your expertise, with rates that can go up to $50/hour depending on your skills, experience, and project needs.Take part in a flexible, remote, freelance project that fits around your primary professional or academic commitments.Participate in an advanced AI project and gain valuable experience to enhance your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English.At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI. What we doThe Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleWe’re looking for someone who can design realistic and structured evaluation scenarios for LLM-based agents. You’ll create test cases that simulate human-performed tasks and define gold-standard behavior to compare agent actions against. You’ll work to ensure each scenario is clearly defined, well-scored, and easy to execute and reuse. You’ll need a sharp analytical mindset, attention to detail, and an interest in how AI agents make decisions. Although every project is unique, you might typically:Create structured test cases that simulate complex human workflows.Define gold-standard behavior and scoring logic to evaluate agent actions. Analyze agent logs, failure modes, and decision paths.Work with code repositories and test frameworks to validate your scenarios.Iterate on prompts, instructions, and test cases to improve clarity and difficulty.Ensure that scenarios are production-ready, easy to run, and reusable.How to get startedSimply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone.RequirementsBachelor's and/or Master’s Degree in Computer Science, Software Engineering, Data Science / Data Analytics, Artificial Intelligence / Machine Learning, Computational Linguistics / Natural Language Processing (NLP), Information Systems or other related fields. Background in QA, software testing, data analysis, or NLP annotation.Good understanding of test design principles (e.g., reproducibility, coverage, edge cases).Strong written communication skills in English.Comfortable with structured formats like JSON/YAML for scenario description.Can define expected agent behaviors (gold paths) and scoring logic.Basic experience with Python and JS.Curious and open to working with AI-generated content, agent logs, and prompt-based behavior.Nice to HaveExperience in writing manual or automated test cases.Familiarity with LLM capabilities and typical failure modes.Understanding of scoring metrics (precision, recall, coverage, reward functions).BenefitsContribute on your own schedule, from anywhere in the world. This opportunity allows you to:Get paid for your expertise, with rates that can go up to $30/hour depending on your skills, experience, and project needs.Take part in a flexible, remote, freelance project that fits around your primary professional or academic commitments.Participate in an advanced AI project and gain valuable experience to enhance your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI. What we doThe Mindrift platform, launched and powered by Toloka, connects domain experts with cutting-edge AI projects from innovative tech clients. Our mission is to unlock the potential of GenAI by tapping into real-world expertise from across the globe. Who we're looking forCalling all security researchers, engineers, and penetration testers with a strong foundation in problem-solving, offensive security, and AI-related risk assessment.If you thrive on digging into complex systems, uncovering hidden vulnerabilities, and thinking creatively under constraints, join us! We’re looking for someone who can bring a hands-on approach to technical challenges, whether breaking into systems to expose weaknesses or building secure tools and processes. We value contributors with a passion for continuous learning, experimentation, and adaptability. About the projectWe’re on the hunt for hands-on Python engineers for a new project focused on developing Model Context Protocol (MCP) servers and internal tools for running and evaluating agent behavior. You’ll implement base methods for agent action verification, integrate with internal and client infrastructures, and help fill tooling gaps across the team. What you’ll be doing:Developing and maintaining MCP-compatible evaluation serversImplementing logic to check agent actions against scenario definitionsCreating or extending tools that writers and QAs use to test agentsWorking closely with infrastructure engineers to ensure compatibilityOccasionally helping with test writing or debug sessions when neededAlthough we’re only looking for experts for this current project, contributors with consistent high-quality submissions may receive an invitation for ongoing collaboration across future projects. How to get started:Apply to this post, qualify, and get the chance to contribute to a project aligned with your skills, on your own schedule. Shape the future of AI while building tools that benefit everyone.RequirementsThe ideal contributor will have:4+ years of Python development experience, ideally in backend or toolsSolid experience building APIs, testing frameworks, or protocol-based interfacesUnderstanding of Docker, Linux CLI, and HTTP-based communicationAbility to integrate new tools into existing infrastructuresFamiliarity with how LLM agents are prompted, executed, and evaluatedClear documentation and communication skills - you’ll work with QA and writersWe also value applicants who have:Experience with Model Context Protocol (MCP) or similar structured agent-server interfacesKnowledge of FastAPI or similar async web frameworksExperience working with LLM logs, scoring functions, or sandbox environmentsAbility to support dev environments (devcontainers, CI configs, linters)JS experienceBenefitsGet paid for your expertise, with rates that can go up to $12/hour depending on your skills, experience, and project needs.Take part in a flexible, remote, freelance project that fits around your primary professional or academic commitments.Participate in an advanced AI project and gain valuable experience to enhance your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI. What we doThe Mindrift platform, launched and powered by Toloka, connects domain experts with cutting-edge AI projects from innovative tech clients. Our mission is to unlock the potential of GenAI by tapping into real-world expertise from across the globe. Who we're looking forCalling all security researchers, engineers, and penetration testers with a strong foundation in problem-solving, offensive security, and AI-related risk assessment.If you thrive on digging into complex systems, uncovering hidden vulnerabilities, and thinking creatively under constraints, join us! We’re looking for someone who can bring a hands-on approach to technical challenges, whether breaking into systems to expose weaknesses or building secure tools and processes. We value contributors with a passion for continuous learning, experimentation, and adaptability. About the projectWe’re on the hunt for hands-on Python engineers for a new project focused on developing Model Context Protocol (MCP) servers and internal tools for running and evaluating agent behavior. You’ll implement base methods for agent action verification, integrate with internal and client infrastructures, and help fill tooling gaps across the team. What you’ll be doing:Developing and maintaining MCP-compatible evaluation serversImplementing logic to check agent actions against scenario definitionsCreating or extending tools that writers and QAs use to test agentsWorking closely with infrastructure engineers to ensure compatibilityOccasionally helping with test writing or debug sessions when neededAlthough we’re only looking for experts for this current project, contributors with consistent high-quality submissions may receive an invitation for ongoing collaboration across future projects. How to get started:Apply to this post, qualify, and get the chance to contribute to a project aligned with your skills, on your own schedule. Shape the future of AI while building tools that benefit everyone.RequirementsThe ideal contributor will have:4+ years of Python development experience, ideally in backend or toolsSolid experience building APIs, testing frameworks, or protocol-based interfacesUnderstanding of Docker, Linux CLI, and HTTP-based communicationAbility to integrate new tools into existing infrastructuresFamiliarity with how LLM agents are prompted, executed, and evaluatedClear documentation and communication skills - you’ll work with QA and writersWe also value applicants who have:Experience with Model Context Protocol (MCP) or similar structured agent-server interfacesKnowledge of FastAPI or similar async web frameworksExperience working with LLM logs, scoring functions, or sandbox environmentsAbility to support dev environments (devcontainers, CI configs, linters)JS experienceBenefitsGet paid for your expertise, with rates that can go up to $50/hour depending on your skills, experience, and project needs.Take part in a flexible, remote, freelance project that fits around your primary professional or academic commitments.Participate in an advanced AI project and gain valuable experience to enhance your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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WHO WE ARE: MagicSchool is the premier generative AI platform for teachers. We're just over 2 years old, and more than 7 million teachers from all over the world have joined our platform. Join a top team at a fast growing company that is working towards real social impact. Make an account and try us out at our website and connect with our passionate community on our Wall of Love.The RoleAs a Staff Context Engineer for AI Systems, you'll architect and optimize how MagicSchool's AI agents reason, remember, and operate across complex educational workflows. You'll design the context management systems that determine what information our agents see, how they maintain state across multi-turn interactions, and how they dynamically retrieve knowledge without overwhelming their attention budget ensuring reliable, coherent AI assistance for millions of educators.This is a high-impact IC role where you'll define the technical foundation of how AI agents manage their "mental workspace," mentor engineers on context engineering principles, and ensure our agentic capabilities remain accurate and focused even in extended, complex classroom scenarios.What You'll DoContext Pipeline ArchitectureContext Architecture & Token Optimization: Architect and implement adaptive context curation pipelines that determine what information enters each agent inference step, balancing comprehensiveness with the finite attention budget of LLMs to prevent context rot.Long-Horizon Task Management: Invent and operationalize memory compaction mechanisms and state management patterns that allow agents to maintain coherence across extended teaching workflows (lesson planning, differentiation, assessment creation).Context Evaluation & Monitoring: Design evaluation pipelines that measure retrieval precision, token relevance, and reasoning coherence as context evolves across sessions. Work with the evaluations team on developing frameworks for measuring attention allocation and agent performance degradation.Dynamic Information RetrievalJust-in-Time Knowledge Retrieval: Build dynamic, runtime data fetching systems that enable agents to autonomously pull relevant curriculum content, student data, and educational resources exactly when needed, rather than pre-loading context with unnecessary information.Tooling & Integration DesignTool & Integration Design: Engineer token-efficient tool APIs and retrieval layers where each tool earns its place in the context window through clear utility and minimal overlap, with robust metadata to guide agent decision-making.Cross-Functional & Educational Domain CollaborationCross-Functional Collaboration: Partner with Product, Research, and Education teams to translate complex educational workflows into optimal context configurations, understanding which information signals matter most for different teaching scenarios.Model & Platform Integration: Collaborate with ML researchers and platform engineers to co-design architectures that integrate memory modules, retrieval adapters, and human-in-the-loop correction systems.Mentorship & StandardsTechnical Mentorship: Guide engineers on context engineering patterns, teaching the shift from prompt-first thinking to holistic context management, token budget awareness, and dynamic information curation.What We're Looking ForDeep Systems & AI Experience: 7+ years building distributed systems with at least 2+ years in staff/senior roles. Hands-on experience building LLM applications, agentic systems, or context-heavy AI workflows with clear understanding of transformer architectures and attention mechanisms.Context Engineering Expertise: Demonstrated experience managing context windows, building dynamic retrieval mechanisms, or designing context compaction strategies. Understanding of when context becomes a liability vs. an asset.Technical Stack: Strong coding skills in Python, TypeScript/Node.js. Experience with our stack (TypeScript, Node.js, PostgreSQL, NextJS, Supabase) or similar. Familiarity with LLM APIs (OpenAI, Anthropic, etc.) and their context management patterns.Information Architecture: Understanding of information retrieval, structured data representation, and strategies for organizing knowledge for AI consumption.Educational Context Awareness: Understanding of or interest in how educational content is structured (standards, curricula, taxonomies), privacy requirements (FERPA/COPPA), and how context needs differ across teaching scenarios.Leadership & Impact: Track record of architecting information systems, making high-leverage architectural decisions, and mentoring engineers on sophisticated technical concepts.Nice to HaveExperience with Model Context Protocol (MCP), context window optimization for specific model families, or building context-aware agent frameworksFamiliarity with educational technology platforms, curriculum databases, or EdTech content managementBackground in semantic search or hybrid retrieval systemsExperience with agent evaluation, measuring context quality/relevance, or instrumentation for attention budget trackingKnowledge of curriculum standards, learning progressions, or educational metadata schemas that inform context designApplication Notice:Notice: Priority Deadline and Review Start DatePlease note that applications for this position will be accepted until 1/11/26 - applications received after this date will be reviewed on an intermittent basis. While we encourage early submissions, all applications received by the priority deadline will receive equal consideration. Thank you for your interest, and we look forward to reviewing your application.Why Join Us?Work on cutting-edge AI technology that directly impacts educators and students.Join a mission-driven team passionate about making education more efficient and equitable.Flexibility of working from home, while fostering a unique culture built on relationships, trust, communication, and collaboration with our team - no matter where they live.For full time employees:Unlimited time off to empower our employees to manage their work-life balance. We work hard for our teachers and users, and encourage our employees to rest and take the time they need.Choice of employer-paid health insurance plans so that you can take care of yourself and your family. Dental and vision are also offered at very low premiums.Every employee is offered generous stock options, vested over 4 years.401k match & monthly wellness stipend.Our Values:Educators are Magic:  Educators are the most important ingredient in the educational process - they are the magic, not the AI. Trust them, empower them, and put them at the center of leading change in service of students and families.Joy and Magic: Bring joy and magic into every learning experience - push the boundaries of what’s possible with AI.Community:  Foster community that supports one another during a time of rapid technological change. Listen to them and serve their needs.Innovation:  The education system is outdated and in need of innovation and change - AI is an opportunity to bring equity, access, and serve the individual needs of students better than we ever have before.Responsibility: Put responsibility and safety at the forefront of the technological change that AI is bringing to education.Diversity: Diversity of thought, perspectives, and backgrounds helps us serve the wide audience of educators and students around the world.Excellence:  Educators and students deserve the best - and we strive for the highest quality in everything we do.

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WHO WE ARE: MagicSchool is the premier generative AI platform for teachers. We're just over 2 years old, and more than 7 million teachers from all over the world have joined our platform. Join a top team at a fast growing company that is working towards real social impact. Make an account and try us out at our website and connect with our passionate community on our Wall of Love.The RoleAs a Staff AI Engineer specializing in RAG, Knowledge Graphs, and Memory Systems, you'll architect the information infrastructure that powers MagicSchool's AI agents. You'll design and build the knowledge organization, retrieval, and memory systems that determine what educational content our agents can access, how they navigate complex curriculum relationships, and how they maintain coherent understanding across extended teaching workflows serving millions of educators.This is a high-impact IC role where you'll define how educational knowledge is structured, indexed, embedded, and retrieved for AI consumption, mentor engineers on advanced retrieval and graph systems, and ensure our agents can reason over rich educational content with precision and reliability.What You'll DoKnowledge Graph & Semantic ArchitectureKnowledge Graph Design: Architect and implement graph-based knowledge systems (Neo4j, Neptune, etc) that represent educational content relationships, standards alignments, prerequisite chains, curriculum coherence, learning progressions, and pedagogical connections. Thus enabling agents to reason over structured educational knowledge.Graph Schema & Ontology Development: Design and evolve ontologies and schemas for educational content, defining entity types (standards, concepts, skills, assessments), relationship semantics, and property models that support both human comprehension and AI reasoning.GraphRAG Implementation: Build GraphRAG systems that combine knowledge graph traversal with vector similarity, enabling agents to retrieve not just similar content but contextually connected educational materials through semantic and structural relationships.Retrieval Pipeline ArchitectureAdvanced RAG Systems: Architect and implement sophisticated retrieval-augmented generation pipelines including hybrid search (dense + sparse), multi-stage retrieval, reranking strategies, and query understanding that surface the most relevant educational content for agent reasoning.Embedding & Vectorization Strategy: Design and operationalize embedding pipelines for educational content, selecting and fine-tuning embedding models, implementing chunking strategies appropriate for curriculum materials, and managing vector stores at scale for fast, accurate retrieval.Retrieval Evaluation & Optimization: Design evaluation pipelines that measure retrieval precision, recall, MRR, and NDCG across educational content types. Continuously optimize retrieval quality through experimentation with embedding models, chunking strategies, and ranking algorithms.Document Ingestion & ProcessingContent Ingestion Pipelines: Build robust ingestion systems that process structured (standards documents, curriculum frameworks, JSON) and unstructured (PDFs, lesson plans, textbooks) educational content, extracting entities, relationships, and metadata for knowledge base population.Semantic Parsing & Extraction: Implement NLP pipelines for educational content that extract key concepts, prerequisite relationships, learning objectives, and pedagogical metadata, enriching raw content with structured annotations for improved retrieval and reasoning.Memory & Context ManagementLong-Horizon Memory Systems: Invent and operationalize memory compaction mechanisms, session state management, and cross-conversation memory patterns that allow agents to maintain coherence across extended teaching workflows while respecting token budgets.Context Evaluation & Monitoring: Design evaluation frameworks that measure retrieval precision, token relevance, attention allocation, and reasoning coherence as context evolves across sessions. Work with the evaluations team on detecting context degradation and retrieval failures.Cross-Functional & Educational Domain CollaborationCross-Functional Collaboration: Partner with Product, Research, and Educators to understand content relationships, retrieval requirements, and context needs across different teaching scenarios, translating domain expertise into technical architecture.Model & Platform Integration: Collaborate with ML researchers / evaluations team and context engineers to co-design architectures that integrate knowledge graphs, vector stores, and retrieval systems with agent runtimes and LLM inference pipelines.Mentorship & StandardsTechnical Mentorship: Guide engineers on knowledge graph design, RAG architecture patterns, embedding strategies, and retrieval optimization, elevating the team's capability in building knowledge-intensive AI systems.What We're Looking ForDeep Knowledge Systems Experience: 5+ years building large-scale information systems with at least 2+ years in staff/senior roles. Extensive hands-on experience with RAG systems, knowledge graphs, or semantic search platforms in production environments.Graph Database Expertise: Deep experience with graph databases (Neo4j, Neptune, or similar), including schema design, query optimization (Cypher, Gremlin), and building graph-based applications. Understanding of when graph structures provide advantages over relational or vector-only approaches.RAG & Retrieval Mastery: Demonstrated expertise building production RAG systems including embedding selection, chunking strategies, hybrid search, reranking, and retrieval evaluation. Familiarity with vector databases (pgvector, Pinecone, Weaviate, Qdrant) and their performance characteristics.Embedding & NLP Background: Strong understanding of embedding models (sentence transformers, domain-specific embeddings), fine-tuning approaches, and semantic similarity. Experience with document processing, entity extraction, and text chunking for optimal retrieval.Technical Stack: Strong coding skills in Python and/or TypeScript/Node.js. Experience with our stack (TypeScript, Node.js, PostgreSQL, NextJS, Supabase) plus graph databases and vector stores. Familiarity with LLM APIs and context management patterns.Information Architecture: Deep understanding of information retrieval theory, semantic search, knowledge representation, and strategies for organizing complex domain knowledge for both human and AI consumption.Leadership & Impact: Track record of architecting complex knowledge systems, making high-leverage technical decisions about information architecture, and mentoring engineers on sophisticated retrieval and graph concepts.Nice to HaveEducational Context Awareness: Understanding of or interest in how educational content is structured (standards, curricula, learning progressions), curriculum relationships, and how knowledge organization differs across teaching scenarios.Experience with GraphRAG, knowledge graph embeddings (node2vec, TransE), or graph neural networks for link prediction and entity resolutionFamiliarity with educational knowledge graphs, standards alignment systems (CASE framework), or EdTech content taxonomiesBackground in semantic web technologies (RDF, OWL, SPARQL), ontology engineering, or knowledge graph construction from unstructured textExperience with model context protocol (MCP) for tool-based retrieval, or building context-aware agent frameworksKnowledge of curriculum standards, learning science, or educational metadata schemas (LOM, schema.org/LearningResource)Experience with fine-tuning embedding models for domain-specific retrieval or building learned sparse retrieversApplication Notice:Notice: Priority Deadline and Review Start DatePlease note that applications for this position will be accepted until 1/11/26 - applications received after this date will be reviewed on an intermittent basis. While we encourage early submissions, all applications received by the priority deadline will receive equal consideration. Thank you for your interest, and we look forward to reviewing your application.Why Join Us?Work on cutting-edge AI technology that directly impacts educators and students.Join a mission-driven team passionate about making education more efficient and equitable.Flexibility of working from home, while fostering a unique culture built on relationships, trust, communication, and collaboration with our team - no matter where they live.For full time employees:Unlimited time off to empower our employees to manage their work-life balance. We work hard for our teachers and users, and encourage our employees to rest and take the time they need.Choice of employer-paid health insurance plans so that you can take care of yourself and your family. Dental and vision are also offered at very low premiums.Every employee is offered generous stock options, vested over 4 years.401k match & monthly wellness stipend.Our Values:Educators are Magic:  Educators are the most important ingredient in the educational process - they are the magic, not the AI. Trust them, empower them, and put them at the center of leading change in service of students and families.Joy and Magic: Bring joy and magic into every learning experience - push the boundaries of what’s possible with AI.Community:  Foster community that supports one another during a time of rapid technological change. Listen to them and serve their needs.Innovation:  The education system is outdated and in need of innovation and change - AI is an opportunity to bring equity, access, and serve the individual needs of students better than we ever have before.Responsibility: Put responsibility and safety at the forefront of the technological change that AI is bringing to education.Diversity: Diversity of thought, perspectives, and backgrounds helps us serve the wide audience of educators and students around the world.Excellence:  Educators and students deserve the best - and we strive for the highest quality in everything we do.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI.What we do The Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleGenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as an AI Tutor in Coding, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Code generation and code review Prompt evaluation and complex data annotation Training and evaluation of large language models Benchmarking and agent-based code execution in sandboxed environments Working across multiple programming languages Adapting guidelines for new domains and use cases Following project-specific rubrics and requirements Collaborating with project leads, solution engineers, and supply managers on complex or experimental projects Note: Flexibility and quick adaptation to new requirements are essential. How to get started Simply apply to this post, qualify, and get the chance to contribute to projects that match your technical skills, on your own schedule. From coding and automation to fine-tuning AI outputs, you’ll play a key role in advancing AI capabilities and real-world applications.RequirementsYou hold a Bachelor's or Master’s Degree in Computer Science, Software Engineering, Software Development, Computer Engineering, Mobile App Development, Cloud Computing, Data Science, Big Data or other related fields.You have at least 3 years of professional experience in Java 17+, including streams API and concurrent programming.Your level of English is advanced (C1) or above.Hands-on experience with JUnit 5, TestNG, Mockito, and TestContainers.Proficiency with build tools (Maven, Gradle), IDEs (IntelliJ IDEA), and CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI).Experience with the Spring ecosystem (Spring Boot, Spring Data, Spring Security), JPA/Hibernate.Strong understanding of JVM internals, garbage collection, performance optimization, and design patterns.Experience with messaging systems (Kafka, RabbitMQ) and microservices architectures.Practical use of AI-assisted tools for refactoring, performance analysis, and test generation.Familiarity with cloud platforms (AWS, Azure), containers, and Kubernetes.Strong skills in JVM profiling (JProfiler, VisualVM) and debugging.You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines.Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge.BenefitsWhy this freelance opportunity might be a great fit for you? Get paid for your expertise, with rates that can go up to $45/hour depending on your skills, experience, and project needs.Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments.Work on advanced AI projects and gain valuable experience that enhances your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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About the role We’re hiring an AI Architect to sit at the intersection of frontier AI research, product, and go-to-market. You’ll partner closely with ML teams in high-stakes meetings, scope and pitch solutions to top AI labs, and translate research needs (post-training, evals, alignment) into clear product roadmaps and measurable outcomes. You’ll drive end-to-end delivery—partnering with AI research teams and core customers to scope, pilot, and iterate on frontier model improvements—while coordinating with engineering, ops, and finance to translate cutting-edge research into deployable, high-impact solutions. What you’ll do Translate research → product: work with client side researchers on post-training, evals, safety/alignment and build the primitives, data, and tooling they need. Partner deeply with core customers and frontier labs: work hands-on with leading AI teams and frontier research labs to tackle hard, open-ended technical problems related to frontier model improvement, performance, and deployment. Shape and propose model improvement work: translate customer and research objectives into clear, technically rigorous proposals—scoping post-training, evaluation, and safety work into well-defined statements of work and execution plans. Translate research into production impact: collaborate with customer-side researchers on post-training, evaluations, and alignment, and help design the data, primitives, and tooling required to improve frontier models in practice. Own the end-to-end lifecycle: lead discovery, write crisp PRDs and technical specs, prioritize trade-offs, run experiments, ship initial solutions, and scale successful pilots into durable, repeatable offerings. Lead complex, high-stakes engagements: independently run technical working sessions with senior customer stakeholders; define success metrics; surface risks early; and drive programs to measurable outcomes. Partner across Scale: collaborate closely with research (agents, browser/SWE agents), platform, operations, security, and finance to deliver reliable, production-grade results for demanding customers. Build evaluation rigor at the frontier: design and stand up robust evaluation frameworks (e.g., RLVR, benchmarks), close the loop with data quality and feedback, and share learnings that elevate technical execution across accounts. You have Deep technical background in applied AI/ML: 5–10+ years in research, engineering, solutions engineering, or technical product roles working on LLMs or multimodal systems, ideally in high-stakes, customer-facing environments. Hands-on experience with model improvement workflows: demonstrated experience with post-training techniques, evaluation design, benchmarking, and model quality iteration. Ability to work on hard, ambiguous technical problems: proven track record of partnering directly with advanced customers or research teams to scope, reason through, and execute on deep technical challenges involving frontier models. Strong technical fluency: you can read papers, interrogate metrics, write or review complex Python/SQL for analysis, and reason about model-data trade-offs. Executive presence with world-class researchers and enterprise leaders; excellent writing and storytelling. Bias to action: you ship, learn, and iterate. How you’ll work Customer-obsessed: start from real research needs; prototype quickly; validate with data. Cross-functional by default: align research, engineering, ops, and GTM on a single plan; communicate clearly up and down. Field-forward: expect regular customer time and research leads; light travel as needed. What success looks like Clear wins with top labs: pilots that convert to scaled programs with strong eval signals. Reusable alignment & eval building blocks that shorten time-to-value across accounts. Crisp internal docs (PRDs, experiment readouts, exec updates) that drive decisions quickly. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$190,000—$230,000 USDPLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision.  PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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The AI orchestration of your wildest imagination.n8n is the open workflow orchestration platform built for the new era of AI. We give technical teams the freedom of code with the speed of no-code, so they can automate faster, smarter, and without limits. Backed by a fiercely inventive community and 500+ builder-approved integrations, we’re changing the way people bring systems together and scale ideas for impact.Since our founding in 2019, we’ve grown into a diverse team of over 160 - working across Europe and the US, connected by a shared builder spirit and with our centre of gravity in Berlin. Along the way, we’ve:Cultivated a community of more than 650,000 active developers and buildersEarned 145k+ GitHub stars, making us one of the world’s Top 40 most popular projectsBeen ranked as one of Europe’s most promising privately held SaaS startups (4th in Sifted’s 2025 B2B SaaS Rising 100)Raised $240m to date, from Sequoia’s first German seed to our recent $180m Series C - bringing us to a $2.5bn valuationAnd are grateful for our 94 eNPS score (most companies would call 70 excellent) That’s the company we’ve built. Now we’d love to see what you can build. If you’re applying, try n8n out - whether you’re technical or not - and share a screenshot of your first workflow with us. The easiest place to start is here: app.n8n.cloud/register.We’re in a defining moment of an incredible journey. Come and build with us.As a Senior AI Engineer, you'll drive intelligent features that redefine how users build automations. You'll build AI-powered capabilities, from natural language input to smart suggestions, that make creating workflows faster and more intuitive.You'll collaborate across engineering, product, and design to bring generative AI and LLM-based enhancements into the core user experience. You'll improve existing AI integrations, develop new ones, and shape how AI powers our product. You’ll work across the entire AI feature lifecycle:Architect and implement AI-powered capabilities: code generation, intelligent node creation, and workflow optimizationIntegrate LLM APIs and embedding models for text-to-workflow and natural language code suggestionsDesign and iterate on prompts to improve model output and user experienceBuild internal tooling, evaluation benchmarks, and automated testing for AI componentsCollaborate closely with other engineers to ensure AI features are reliable, performant, and scalableBalance experimentation with impact: ship quickly while focusing on user valueStay current with advances in LLMs, prompt frameworks, and developer tools - and bring those insights into our roadmapRequirements5+ years of experience building web-based products, ideally in B2B SaaS startupsStrong fullstack development skills with TypeScript, Node.js, and API designExperience shipping AI-powered features in production with LLM APIs (OpenAI, Anthropic, etc.) and understanding of how to translate machine intelligence into user value. We're looking for experience building end-to-end systems.Understanding of AI fundamentals: agent architectures, chat completion roles, embedding vectors, vector databases, and chunking strategiesHands-on experience with prompt engineering, embedding models, and vector storesA user-focused mindset: you care about delivering features that solve real problemsA bias for shipping and learning - fast iteration is second nature to youBonus Points ForExperience fine-tuning LLMs or working with retrieval-augmented generation (RAG) systemsFrontend experience using Vue or ReactTechnical writing or documentation contributions, especially around developer tools or AIExperience with agent orchestration patterns and state management in multi-step AI systemsKnowledge of code quality evaluation metrics and context optimization techniquesn8n is an equal opportunity employer and does not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, gender identity, age, marital status, veteran status, or disability status.We can sponsor visas to Germany; for any other country, you need to have existing right to work.Our company language is English.You care about diversity and inclusion? We do too! Check out our Diversity, Inclusion and Belonging initiatives at n8n (https://www.notion.so/n8n/Diversity-inclusion-and-belonging-n8n-c1bec2fff536422d868b1a438d990e35).Location disclaimer: If you see multiple job postings for the same role, it is most likely because we're hiring remotely for this role and posting in different locations to make sure every potential candidate can see the role. Please apply to the location you're the most likely to work from in the future. Benefits Competitive compensation 💸 – We offer fair and attractive pay.Ownership 💪 – Our core value is to “empower others,” and we mean it—you’ll get a slice of n8n with equity.Work/life balance 🏖️ – We work hard but ensure you have time to recharge:Europe: 30 days of vacation, plus public holidays wherever you are.US: 15 vacation days, 8 sick days, plus public holidays wherever you are.Health & wellness 🩺 –Europe: We provide benefits according to local country norms.*US: Multiple low-premium, low-deductible medical plans with coverage for individuals and families—plus a no-cost premium HDHP option with a pre-seeded HSA—along with dental and vision coverage.Future planning 💰 –Europe: We provide pension contributions according to local country norms.*US: 401(k) retirement plan with a 4% employer match.Financial security 🛡️ –Europe: We provide benefits according to local country norms.*US: Company-paid short-term and long-term disability insurance, plus life insurance to support you and your loved ones.Career growth 📈 – We hire rising stars who grow with us! You’ll get €1K (or equivalent) per year to spend on courses, books, events, or coaching to level up your skills.A passionate team 🤩 – We love our product, and we prove it with regular hackathons where we see who can build the coolest thing with it!Remote-first 🌏 – Our team works remotely across Europe, with regular off-sites for team bonding. Some roles, like sales in the US, are hybrid—please check the job description.Giving back 🤝 – We're big fans of open source, and you'll get $100 per month to support projects you care about.AI enablement 🤖 – We believe in working smarter—everyone gets an unlimited AI budget to explore and use the best tools to boost productivity and creativity.Transparency 🙏 – We all know what everyone’s working on, how the company is doing—the whole shebang.An ambitious but kind culture 😍 – People love working here—our eNPS for 2024 is 94!* Country-specific details are provided in your contract.