{"has_next":true,"jobs":[{"id":"f715bbfc-6fe4-49dc-a487-ca349270ef1e","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Senior AI Product Engineer 2, Control Monitoring","slug":"senior-ai-product-engineer-2-control-monitoring-71c698cf","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata is reimagining compliance as an intelligent, always-on experience — and AI is at the center of that vision. We are seeking a Senior AI Product Engineer to own the full-stack development of customer-facing AI features, embedded directly within our product teams. This is not a platform or infrastructure role. You'll translate the capabilities of LLMs, agents, and RAG pipelines into intuitive, polished product experiences — streaming chat interfaces, agentic workflows, intelligent summaries, and guided automation that makes compliance feel effortless. You'll partner closely with AI Engineers who own the backend intelligence and Product and Design who shape the vision, but you are the engineer who closes the loop between AI capability and the customer experience.\n\nWhat you'll do:\n\n - Build AI-powered product features end-to-end — React/TypeScript UI through Node.js/Python backend — with real-time streaming, graceful degradation, and human-in-the-loop interaction patterns\n\n - Translate AI capabilities — RAG pipelines, agentic workflows, structured reasoning — into interactions that feel natural to compliance practitioners\n\n - Partner with AI Engineers to define API contracts and output schemas; translate RAG pipelines, agentic workflows, and structured reasoning into interactions that feel natural to compliance practitioners\n\n - Advocate for the user's perspective in technical decisions; surface where model outputs break down in practice and iterate the product layer accordingly\n\n - Build user-facing feedback loops that capture signal on AI output quality and make it actionable for the broader AI team\n\n - Instrument AI features with product-level observability — latency, engagement, task completion, drop-off — alongside integration and end-to-end tests that validate behavior across the full stack\n\n - Establish reusable patterns (streaming hooks, feedback components, AI state management) that accelerate future AI feature development\n\n - Mentor engineers newer to AI product development; participate in design reviews with both engineering depth and product instinct\n\nWhat you'll bring:\n\n - Experience: 7+ years of software engineering experience with a proven track record of shipping full-stack features in production; 2+ years working on AI-powered product features\n\n - Frontend: Strong proficiency in React and TypeScript; experience building responsive, interactive UIs that handle async, streaming, and real-time data gra","salary_min":192000,"salary_max":259800,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["llm","rag","agents","healthcare"],"apply_url":"https://jobs.ashbyhq.com/drata/03b2d32a-b1af-4a67-8239-5ae3abcc2118/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-30T00:39:16.165Z","expires_at":"2026-06-29T14:13:57.394601Z","created_at":"2026-05-30T14:13:57.508695Z","updated_at":"2026-05-30T14:13:57.508695Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f715bbfc-6fe4-49dc-a487-ca349270ef1e"},{"id":"bd9bd8db-eb19-4a9e-a4f1-4cb669ecf36f","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Senior AI Product Engineer 2, Control Remidiation","slug":"senior-ai-product-engineer-2-control-remidiation-573aad92","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata is reimagining compliance as an intelligent, always-on experience — and AI is at the center of that vision. We are seeking a Senior AI Product Engineer to own the full-stack development of customer-facing AI features, embedded directly within our product teams. This is not a platform or infrastructure role. You'll translate the capabilities of LLMs, agents, and RAG pipelines into intuitive, polished product experiences — streaming chat interfaces, agentic workflows, intelligent summaries, and guided automation that makes compliance feel effortless. You'll partner closely with AI Engineers who own the backend intelligence and Product and Design who shape the vision, but you are the engineer who closes the loop between AI capability and the customer experience.\n\nWhat you'll do:\n\n - Build AI-powered product features end-to-end — React/TypeScript UI through Node.js/Python backend — with real-time streaming, graceful degradation, and human-in-the-loop interaction patterns\n\n - Translate AI capabilities — RAG pipelines, agentic workflows, structured reasoning — into interactions that feel natural to compliance practitioners\n\n - Partner with AI Engineers to define API contracts and output schemas; translate RAG pipelines, agentic workflows, and structured reasoning into interactions that feel natural to compliance practitioners\n\n - Advocate for the user's perspective in technical decisions; surface where model outputs break down in practice and iterate the product layer accordingly\n\n - Build user-facing feedback loops that capture signal on AI output quality and make it actionable for the broader AI team\n\n - Instrument AI features with product-level observability — latency, engagement, task completion, drop-off — alongside integration and end-to-end tests that validate behavior across the full stack\n\n - Establish reusable patterns (streaming hooks, feedback components, AI state management) that accelerate future AI feature development\n\n - Mentor engineers newer to AI product development; participate in design reviews with both engineering depth and product instinct\n\nWhat you'll bring:\n\n - Experience: 7+ years of software engineering experience with a proven track record of shipping full-stack features in production; 2+ years working on AI-powered product features\n\n - Frontend: Strong proficiency in React and TypeScript; experience building responsive, interactive UIs that handle async, streaming, and real-time data gra","salary_min":192000,"salary_max":259800,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["llm","agents","healthcare","rag"],"apply_url":"https://jobs.ashbyhq.com/drata/760b5a7c-a532-44e4-9ee3-89a60669eaa2/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-30T00:39:13.31Z","expires_at":"2026-06-29T14:13:57.47465Z","created_at":"2026-05-30T14:13:57.593994Z","updated_at":"2026-05-30T14:13:57.593994Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/bd9bd8db-eb19-4a9e-a4f1-4cb669ecf36f"},{"id":"00aeda19-ef93-4590-8fa9-dca46238d0f1","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Senior AI Product Engineer 2, Evidence","slug":"senior-ai-product-engineer-2-evidence-92d9f168","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata is reimagining compliance as an intelligent, always-on experience — and AI is at the center of that vision. We are seeking a Senior AI Product Engineer to own the full-stack development of customer-facing AI features, embedded directly within our product teams. This is not a platform or infrastructure role. You'll translate the capabilities of LLMs, agents, and RAG pipelines into intuitive, polished product experiences — streaming chat interfaces, agentic workflows, intelligent summaries, and guided automation that makes compliance feel effortless. You'll partner closely with AI Engineers who own the backend intelligence and Product and Design who shape the vision, but you are the engineer who closes the loop between AI capability and the customer experience.\n\nWhat you'll do:\n\n - Build AI-powered product features end-to-end — React/TypeScript UI through Node.js/Python backend — with real-time streaming, graceful degradation, and human-in-the-loop interaction patterns\n\n - Translate AI capabilities — RAG pipelines, agentic workflows, structured reasoning — into interactions that feel natural to compliance practitioners\n\n - Partner with AI Engineers to define API contracts and output schemas; translate RAG pipelines, agentic workflows, and structured reasoning into interactions that feel natural to compliance practitioners\n\n - Advocate for the user's perspective in technical decisions; surface where model outputs break down in practice and iterate the product layer accordingly\n\n - Build user-facing feedback loops that capture signal on AI output quality and make it actionable for the broader AI team\n\n - Instrument AI features with product-level observability — latency, engagement, task completion, drop-off — alongside integration and end-to-end tests that validate behavior across the full stack\n\n - Establish reusable patterns (streaming hooks, feedback components, AI state management) that accelerate future AI feature development\n\n - Mentor engineers newer to AI product development; participate in design reviews with both engineering depth and product instinct\n\nWhat you'll bring:\n\n - Experience: 7+ years of software engineering experience with a proven track record of shipping full-stack features in production; 2+ years working on AI-powered product features\n\n - Frontend: Strong proficiency in React and TypeScript; experience building responsive, interactive UIs that handle async, streaming, and real-time data gra","salary_min":192000,"salary_max":259800,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["healthcare","rag","llm","agents"],"apply_url":"https://jobs.ashbyhq.com/drata/855d1119-f88e-4421-b0f3-884926f48a21/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-30T00:39:10.289Z","expires_at":"2026-06-29T14:13:57.315024Z","created_at":"2026-05-30T14:13:57.429903Z","updated_at":"2026-05-30T14:13:57.429903Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/00aeda19-ef93-4590-8fa9-dca46238d0f1"},{"id":"ef3a3333-a3b2-413d-9313-7ffff60ec3fd","company_id":"01048ffd-9864-41e0-a719-14b849fbcbcd","title":"Principal AI Engineer, Special Programs","slug":"principal-ai-engineer-special-programs-cdf31fea","description":"SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today SpaceX is actively developing the technologies to make this possible, with the ultimate goal of enabling human life on Mars.\n PRINCIPAL AI ENGINEER, SPECIAL PROGRAMS \n This team focuses on engineering and deploying AI capabilities (models, APIs, tools, and integrations) for U.S. federal agencies. You'll work closely with product, research, infrastructure, and legal/governance teams to make  AI and future models maximally useful for missions while upholding safety, transparency, and ethical standards.\n RESPONSIBILITIES: \n \n Design, build, and optimize integrations between AI frontier models (e.g., Grok family) and government systems, platforms, and data environments\n Collaborate on custom SDKs, APIs, developer tools, and documentation tailored for government and enterprise developers\n Partner with agency stakeholders to understand requirements, prototype solutions, and iterate rapidly based on real-world feedback\n Ship production-grade code and features with a bias toward speed, simplicity, and measurable impact\n \n BASIC QUALIFICATIONS: \n \n Bachelor's degree in computer science or another STEM discipline; OR 2+ years of professional experience in software development in lieu of a degree\n 6+ years of hands-on software engineering experience building scalable systems, APIs, or AI/ML applications (strong Python proficiency, other languages a plus)\n \n PREFERRED SKILLS AND EXPERIENCE: \n \n Experience working with large language models, generative AI, or agentic systems—either in research, production, or applied engineering\n Familiarity with government or public sector technology environments (federal civilian agencies, state/local gov, or regulated industries like healthcare, finance, or infrastructure)\n Strong product sensibility: ability to translate ambiguous stakeholder needs into concrete technical solutions\n Demonstrated ability to write clean, maintainable, high-performance code under tight timelines\n Exceptional problem-solving skills and intellectual curiosity—you thrive on hard, ambiguous challenges\n Excellent communication skills; you can explain complex technical concepts to non-technical partners clearly and concisely\n Prior work on AI safety, governance, red-teaming, or responsible AI deployment\n Experience with cloud platforms (AWS, GCP, Azure), containerization (Docker/Kubernetes), or API orchestration\n Background in policy-adjacent technical roles, civic tech, or public-interest technology\n Contributions to open-source AI projects or developer tools\n \n ADDITIONAL REQUIREMENTS: \n \n Must be willing to work extended hours and weekends as needed\n 20% travel may be required to government sites\n This position requires successfully obtaining and maintaining a Top Secret Security Clearance as a condition of employment. While the clearance may not be immediately necessary upon hire, we encourage you to initiate the application process promptly upon accepting this offer. Your ability to secure the necessary clearance is essential for fulfilling key responsibilities of the role. Should you be unable to obtain it, SpaceX reserves the right to modify or terminate your employment to align with operational needs.\n \n COMPENSATION AND BENEFITS: \n Pay range:     Principal AI Engineer: $220,000.00 - $350,000.00/per year    \n Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, and experience.\n Base salary is just one part of your total rewards package at SpaceX. You may also be eligible for long-term incentives, in the form of company stock, stock options, or long-term cash awards, as well as potential discretionary bonuses and the ability to purchase additional stock at a discount through an Employee Stock Purchase Plan. You will also receive access to comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short and long-term disability insurance, life insurance, paid parental leave, and various other discounts and perks. You may also accrue 3 weeks of paid vacation and will be eligible for 10 or more paid holidays per year. Employees accrue paid sick leave pursuant to Company policy which satisfies or exceeds the accrual, carryover, and use requirements of the law.\n ITAR REQUIREMENTS: \n \n To conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder), (iii) Refugee under 8 U.S.C. § 1157, or (iv) Asylee under 8 U.S.C. § 1158, or be eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here .  \n \n SpaceX is an Equal Opportunity Employer; employment with SpaceX is governed on the basis of merit, competence and qualifications and will not be influenced","salary_min":220000,"salary_max":350000,"location":"Palo Alto, CA","workplace":"onsite","job_type":"full-time","experience_level":"principal","tags":["generative-ai","alignment","llm","agents","healthcare"],"apply_url":"https://boards.greenhouse.io/spacex/jobs/8572113002?gh_jid=8572113002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T23:50:00Z","expires_at":"2026-06-29T14:16:59.183347Z","created_at":"2026-05-30T14:16:59.297291Z","updated_at":"2026-05-30T14:16:59.297291Z","company_name":"SpaceX","company_slug":"spacex","company_logo_url":"https://www.google.com/s2/favicons?domain=spacex.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/ef3a3333-a3b2-413d-9313-7ffff60ec3fd"},{"id":"530f705a-007a-497f-9f62-9a6e196ea9ad","company_id":"1df860e2-0800-48ea-81af-7121965be17a","title":"Engineering Manager - Machine Learning","slug":"engineering-manager-machine-learning-e1742de5","description":"Your work will change lives. Including your own. \n \n The Impact You’ll Make \n You will lead a team working to build, scale, and optimize the machine learning infrastructure that powers Recursion's drug discovery platform. From model training pipelines to production deployment systems, to agent infrastructure and Large Language Models, you will ensure our ML models can operate at massive scale across our supercomputing infrastructure, both on prem and in the cloud. You will work cross-functionally across ML engineering, data science, and research teams to translate requirements into robust, scalable ML infrastructure solutions.\n In This Role You Will: \n \n Enable AI/ML, LLM, and Agentic Systems teams for scale - The ML infrastructure team is responsible for building and operating platforms that allow data scientists and ML engineers to train, deploy, and monitor models across Recursion's massive datasets. With billions of compounds, 30+ petabytes of experimental data, and complex deep learning workloads, your team enables everything from automated compound screening models to clinical trial prediction systems. You will work closely with researchers and ML engineers to understand their infrastructure needs and build scalable solutions for model development, training, and deployment.\n Act as a mentor, coach, and sponsor - You will share your technical, leadership and managerial skills in MLOps, distributed computing, and infrastructure engineering, delivering impact, learning, and growth across teams at Recursion. We believe that the best work comes from working across organizational boundaries and you will have opportunities to partner with ML research, platform engineering, and business teams.\n Enable a model-driven culture - Machine learning is at the core of everything we do. You will work with stakeholders across the business to ensure our ML infrastructure supports rapid experimentation, reliable model deployment, and continuous improvement. Problems you will work on could range from optimizing GPU cluster utilization to implementing Agentic orchestration and establishing company-wide MLOps standards\n \n The Team You’ll Join: \n You'll be part of a group of technical leaders who work together on the craft of engineering leadership as well as debate ML system architecture, MLOps patterns, and infrastructure optimization strategies. We all work better when we have the support of those around us and are learning together to solve complex problems around model scalability, deployment reliability, and infrastructure efficiency across our teams. You will report to the Executive Director of Engineering who broadly oversees Cloud Infrastructure, High Performance Compute and Machine Learning Infrastructure space.\n The Experience You Will Need: \n \n Experience in a hands-on technical role as a tech lead or a manager with a focus on infrastructure, MLOps and distributed systems. Excitement for deeply engaging in technical details with your team around machine learning, orchestration and agentic systems.\n A people-first mindset. We deliver in a way that prioritizes supporting our coworkers in their growth and experience and understand how Conway's Law shapes our ML system outcomes.\n Demonstrated past record of learning from and teaching peers in areas of ML infrastructure, model deployment, distributed compute, GPU optimization, and MLOps system architecture\n Excitement to learn parts of our ML tech stack that you might not already know. Our current ML infrastructure includes: Python, PyTorch, Docker, Kubernetes, Ray, Weights \u0026 Biases, Prefect, BigQuery, Postgres, GCP, CUDA, and various model serving frameworks.\n Fluency in life sciences or drug discovery is a plus but not required to be considered.\n \n Working Location \u0026 Compensation: \n This is a remote position based in Toronto, Canada. \n At Recursion, we believe that every employee should be compensated fairly. Based on the skill and level of experience required for this role, the estimated current annual base range for this role is $210,070 to $282,851 (CAD) . You will also be eligible for an annual bonus and equity compensation, as well as a comprehensive benefits package. \n #LI-EP1\n The Values We Hope You Share: \n \n We act boldly with integrity. We are unconstrained in our thinking, take calculated risks, and push boundaries, but never at the expense of ethics, science, or trust. \n We care deeply and engage directly. Caring means holding a deep sense of responsibility and respect - showing up, speaking honestly, and taking action.\n We learn actively and adapt rapidly. Progress comes from doing. We experiment, test, and refine, embracing iteration over perfection.\n We move with urgency because patients are waiting. Speed isn’t about rushing but about moving the needle every day.\n We take ownership and accountability. Through ownership and accountability, we enable trust and autonomy—leaders take accountability for decisive action, and teams own outcomes ","salary_min":210070,"salary_max":282851,"location":"Toronto, Canada","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["distributed-systems","agents","mlops","gpu","healthcare","deep-learning","pytorch","llm"],"apply_url":"https://job-boards.greenhouse.io/recursionpharmaceuticals/jobs/7961536","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T14:56:14Z","expires_at":"2026-06-29T14:07:04.607932Z","created_at":"2026-05-30T14:07:04.722791Z","updated_at":"2026-05-30T14:07:04.722791Z","company_name":"Recursion","company_slug":"recursion","company_logo_url":"https://www.google.com/s2/favicons?domain=recursion.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/530f705a-007a-497f-9f62-9a6e196ea9ad"},{"id":"58a5e82c-4cbd-49e1-9ce2-45a7b213b0a9","company_id":"1df860e2-0800-48ea-81af-7121965be17a","title":"Engineering Manager - Machine Learning","slug":"engineering-manager-machine-learning-288c8ba8","description":"Your work will change lives. Including your own. \n \n The Impact You’ll Make \n You will lead a team working to build, scale, and optimize the machine learning infrastructure that powers Recursion's drug discovery platform. From model training pipelines to production deployment systems, to agent infrastructure and Large Language Models, you will ensure our ML models can operate at massive scale across our supercomputing infrastructure, both on prem and in the cloud. You will work cross-functionally across ML engineering, data science, and research teams to translate requirements into robust, scalable ML infrastructure solutions.\n In This Role You Will: \n \n Enable AI/ML, LLM, and Agentic Systems teams for scale - The ML infrastructure team is responsible for building and operating platforms that allow data scientists and ML engineers to train, deploy, and monitor models across Recursion's massive datasets. With billions of compounds, 30+ petabytes of experimental data, and complex deep learning workloads, your team enables everything from automated compound screening models to clinical trial prediction systems. You will work closely with researchers and ML engineers to understand their infrastructure needs and build scalable solutions for model development, training, and deployment.\n Act as a mentor, coach, and sponsor - You will share your technical, leadership and managerial skills in MLOps, distributed computing, and infrastructure engineering, delivering impact, learning, and growth across teams at Recursion. We believe that the best work comes from working across organizational boundaries and you will have opportunities to partner with ML research, platform engineering, and business teams.\n Enable a model-driven culture - Machine learning is at the core of everything we do. You will work with stakeholders across the business to ensure our ML infrastructure supports rapid experimentation, reliable model deployment, and continuous improvement. Problems you will work on could range from optimizing GPU cluster utilization to implementing Agentic orchestration and establishing company-wide MLOps standards\n \n The Team You’ll Join: \n You'll be part of a group of technical leaders who work together on the craft of engineering leadership as well as debate ML system architecture, MLOps patterns, and infrastructure optimization strategies. We all work better when we have the support of those around us and are learning together to solve complex problems around model scalability, deployment reliability, and infrastructure efficiency across our teams. You will report to the Executive Director of Engineering who broadly oversees Cloud Infrastructure, High Performance Compute and Machine Learning Infrastructure space.\n The Experience You Will Need: \n \n Experience in a hands-on technical role as a tech lead or a manager with a focus on infrastructure, MLOps and distributed systems. Excitement for deeply engaging in technical details with your team around machine learning, orchestration and agentic systems.\n A people-first mindset. We deliver in a way that prioritizes supporting our coworkers in their growth and experience and understand how Conway's Law shapes our ML system outcomes.\n Demonstrated past record of learning from and teaching peers in areas of ML infrastructure, model deployment, distributed compute, GPU optimization, and MLOps system architecture\n Excitement to learn parts of our ML tech stack that you might not already know. Our current ML infrastructure includes: Python, PyTorch, Docker, Kubernetes, Ray, Weights \u0026 Biases, Prefect, BigQuery, Postgres, GCP, CUDA, and various model serving frameworks.\n Fluency in life sciences or drug discovery is a plus but not required to be considered.\n \n Working Location \u0026 Compensation: \n This is an office-based, hybrid position at our US headquarters located in Salt Lake City, Utah . Employees are expected to work in the office at least 50% of the time.\n At Recursion, we believe that every employee should be compensated fairly. Based on the skill and level of experience required for this role, the estimated current annual base range for this role is $151,130 to $203,490 (USD) . You will also be eligible for an annual bonus and equity compensation, as well as a comprehensive benefits package. \n #LI-EP1\n The Values We Hope You Share: \n \n We act boldly with integrity. We are unconstrained in our thinking, take calculated risks, and push boundaries, but never at the expense of ethics, science, or trust. \n We care deeply and engage directly. Caring means holding a deep sense of responsibility and respect - showing up, speaking honestly, and taking action.\n We learn actively and adapt rapidly. Progress comes from doing. We experiment, test, and refine, embracing iteration over perfection.\n We move with urgency because patients are waiting. Speed isn’t about rushing but about moving the needle every day.\n We take ownership and accountability. Through ownership and acco","salary_min":151130,"salary_max":203490,"location":"Salt Lake City, Utah","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["pytorch","deep-learning","cloud","mlops","gpu","llm","distributed-systems","healthcare"],"apply_url":"https://job-boards.greenhouse.io/recursionpharmaceuticals/jobs/7961460","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T14:56:13Z","expires_at":"2026-06-29T14:07:04.532978Z","created_at":"2026-05-30T14:07:04.642889Z","updated_at":"2026-05-30T14:07:04.642889Z","company_name":"Recursion","company_slug":"recursion","company_logo_url":"https://www.google.com/s2/favicons?domain=recursion.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/58a5e82c-4cbd-49e1-9ce2-45a7b213b0a9"},{"id":"a702d67f-523f-4f26-a10d-c872f90afda6","company_id":"b6e5a3d1-9bde-4a82-8d78-9f38ed99ee81","title":"Staff Applied Scientist - Agentic Interfaces","slug":"staff-applied-scientist-agentic-interfaces-72926417","description":"Team description \n At Datadog, AI agents are becoming first-class consumers of observability, security, and software delivery data — from third-party coding agents like Claude Code, Cursor, and Copilot, to our own Bits SRE, Bits Assistant, and Bits Dev Agent. The Agentic Interfaces team owns the platform that connects these agents to Datadog: the MCP Server, the tools and retrieval surfaces agents call into, and — critically — the evaluation systems that tell us whether an agent's experience on Datadog data is actually getting better over time.\n This role is about that last piece. We're hiring a Staff Applied Scientist to define what \"good\" means for an Agentic interface at Datadog and to build the measurement systems that make it true. \"Good\" isn't one number — it spans answer quality, tool-selection accuracy, retrieval relevance, latency, token cost, and end-to-end agent success on real customer workflows. You'll design the evals, build the datasets, define the metrics, and partner with the AI engineers on the team to land the platform that lets every product group at Datadog ship integrations that are demonstrably better release over release.\n The space is full of open research questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when the tool catalog has hundreds of entries and grows weekly? How do you build a measurement system that catches regressions across first-party and third-party agents at once, without each team writing their own harness? If those are the problems you want to spend your time on, come build this with us.\n Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. \n  \n What You’ll Do: \n \n \n Own the evaluation strategy for Datadog's AI agent integrations. Define the metrics — offline and online, quality and cost, single-turn and trajectory-level — that the team and the broader organization optimize against.\n \n Build the eval datasets, golden traces, and regression harnesses that catch quality changes before they hit customers, and make those assets reusable by every team contributing tools to the platform.\n \n Drive measurable improvements to retrieval relevance, tool-selection accuracy, and context efficiency, partnering closely with the AI engineers on the team who build the underlying platform.\n \n Run applied research on the open problems in agent–data interaction: tool selection under large catalogs, multi-turn agent evaluation, grounding and hallucination control on live telemetry, cost/quality tradeoffs at scale.\n \n Partner with the Bits SRE, Bits Assistant, and Bits Dev Agent teams so first-party agents benefit from the same measurement substrate as third-party integrations, and so learnings move freely in both directions.\n \n Provide technical leadership across the Agentic Interfaces team and the broader organization through design reviews, working groups, and mentorship, and represent the team externally through talks, blog posts, and contributions to the open agent ecosystem.\n \n Who You Are: \n \n \n You have a BS/MS/PhD in a scientific field, or equivalent experience.\n \n 10+ years of relevant engineering or applied science experience, including time as a technical lead.\n \n Proven track record of leading ML or GenAI initiatives in a product-driven environment, from research through production.\n \n Significant experience with evaluation, experimentation, or measurement of ML systems at scale.\n \n You bring a strong product mindset and are comfortable driving initiatives across cross-functional teams.\n \n You thrive in ambiguity and can make sound technical calls when the path isn’t yet defined.\n \n Benefits and Growth: \n \n \n New hire stock equity (RSUs) and employee stock purchase plan (ESPP)\n \n Continuous professional development, product training, and career pathing\n \n An inclusive company culture, giving programs, and the ability to join our Community Guilds (Datadog employee resource groups)\n Competitive global benefits and global Spring Health benefits for employees and dependents age 6+\n \n #LI-Onsite\n Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.\n The reasonably estimated yearly salary for this role at Datadog is:\n $276,000 — $345,000 USD \n \n About Datadog:  \n Datadog is the leading observability and security platform for the AI era, providing businesses with ","salary_min":276000,"salary_max":345000,"location":"New York, NY","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["healthcare","agents","generative-ai","code-generation"],"apply_url":"https://careers.datadoghq.com/detail/7964141/?gh_jid=7964141","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T14:06:44Z","expires_at":"2026-06-29T14:03:24.031594Z","created_at":"2026-05-29T14:09:23.831464Z","updated_at":"2026-05-30T14:03:24.142868Z","company_name":"Datadog","company_slug":"datadog","company_logo_url":"https://www.google.com/s2/favicons?domain=datadoghq.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a702d67f-523f-4f26-a10d-c872f90afda6"},{"id":"a5365758-6ce5-460b-996c-bbaaa2aa3d6e","company_id":"a0000000-0000-0000-0000-000000000001","title":"Implementation Specialist ","slug":"implementation-specialist-35e895af","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the Role: \n We're building a team of Implementation Specialists to be the technical hands that switch Claude on inside our largest customers — the people who turn \"we've signed the contract\" into \"our employees can log in, with the right access, under the right policies, the way our security team expects.\" Before any CSM can drive adoption, before any Technical Specialist can run a workshop, before any champion can ship their first workflow, someone has to connect Claude to the customer's identity provider, get the right people provisioned into the right workspaces, and walk their CISO through how it all comes together. That's your work.\n This is not an adoption or enablement role — those sit with our Customer Success Managers and Technical Specialists. Your job is technical deployment, security credibility, and clean handoffs. You'll spend your time inside customer identity providers — Okta, Entra ID, Ping, Google Workspace — on working sessions with customer IT and IAM leads, debugging SAML assertions and SCIM attribute mappings, and authoring the runbooks that make every downstream hour of CS and Enablement investment compound instead of evaporate.\n You should be the kind of person a customer's security lead wants in the room — credible because you've shipped dozens of enterprise deployments, calm under pressure because you've debugged every flavor of IdP edge case, and trusted because when you say \"we can do that\" or \"we won't do that, here's why,\" your word holds.\n What you'll do: \n You'll typically run a portfolio of 5–10 concurrent enterprise deployments. A week looks roughly like:\n \n \n Configure and troubleshoot SSO (SAML, OIDC), SCIM/JIT provisioning, MCP connectors, admin policy templates, and seat-assignment logic across Okta, Entra ID, Ping, and Google Workspace observed as part of setup. Deliver informative transitions to Support for deeper issues that require investigation and/or engineering support\n \n Run technical working sessions with customer IT, IAM, and security leads — including CISOs at F500 scale — explaining our security model, shared-responsibility boundaries, and data-handling posture.\n \n Anticipate what a regulated customer's security review will ask (SOC 2, ISO 27001, HIPAA, FedRAMP) and partner with our AI Security Specialist when needed.\n \n Diagnose identity edge cases live on calls: broken SAML assertions, misconfigured SCIM attribute maps, group-filtering issues, tenant-provisioning quirks.\n \n Author Deployment Runbooks that the CSM inherits at handoff — as-built environment, admin contacts, known issues, support tier — so adoption starts warm.\n \n Contribute to repeatable playbooks and admin documentation that shape how the IS function scales — you'll be one of our first hires, so what you build becomes the template.\n \n What we're looking for: \n \n \n 5-7+ years in a customer-facing technical role — Technical Account Managers, Technical Onboarding, Technical Support, Solution Architects or technical consulting.\n \n 4+ years of hands-on, sustained ownership of enterprise identity integration work — SAML, OIDC, SCIM v2, JIT provisioning, across at least two major IdPs (Okta, Entra ID, Ping, Google Workspace) and familiarity with Work OS. You can debug a broken SAML assertion or a misconfigured SCIM attribute map without escalating.\n \n Senior candidates should have experience having led the Implementation Specialist function or built deployment playbooks from scratch at a prior company\n \n Proven track record running multiple concurrent enterprise deployments at F500 scale, with documented handoffs.\n \n Customer-facing technical communication skills that hold up under pressure. You can run a working session with a CISO and an IAM lead in the same room, explain trade-offs without jargon, and hold the line on scope without damaging the relationship.\n \n Working knowledge of enterprise security and compliance frameworks (SOC 2, ISO 27001, HIPAA, FedRAMP) sufficient to anticipate and answer customer security reviews.\n \n Experience in regulated industries: financial services, healthcare, pharma, public sector and with the security-review rigor they require.\n \n Portfolio discipline, you document as you go, you hit milestones you've committed to, and you don't drop balls across 5–10 concurrent threads.\n \n Prior experience at an enterprise SaaS or AI/ LLM vendor with a heavy admin/IdP surface (e.g., identity, collaboration, security, or productivity platforms).\n \n Exposure to AI/LLM products or agentic systems. \n \n Familiarity with Claude specific concepts like Skills, MCP, and Plugins.\n \n Experience partnering with SI / ","salary_min":151840,"salary_max":260000,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["llm","agents","alignment","healthcare"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5233951008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T13:26:26Z","expires_at":"2026-06-29T14:00:16.996946Z","created_at":"2026-05-29T14:00:21.009787Z","updated_at":"2026-05-30T14:00:17.114841Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a5365758-6ce5-460b-996c-bbaaa2aa3d6e"},{"id":"152a9a3c-a62a-4f20-a505-60c62517b468","company_id":"861968d1-d9f8-4217-9873-ce4b24851abc","title":"Machine Learning Scientist, Multimodal AI ","slug":"machine-learning-scientist-multimodal-ai-e50612bb","description":"POSITION SUMMARY: \n Natera is hiring a Machine Learning Scientist to join our AI and computational biology team. This role develops and deploys deep learning models across digital pathology, genomics, transcriptomics, and cell-free DNA (cfDNA) modalities. You will build multimodal AI systems that integrate imaging, molecular, and clinical data, leveraging proprietary genomic and clinical datasets. You will collaborate with scientists, pathologists, bioinformaticians, and software engineers to scale machine learning approaches that advance personalized oncology diagnostics and tumor-informed minimal residual disease (MRD) testing.\n PRIMARY RESPONSIBILITIES: \n \n Design, implement, and evaluate deep learning models across biomedical data modalities, including histopathology imaging, genomic sequencing, transcriptomics, and cfDNA features\n Develop multimodal AI architectures that integrate H\u0026E whole-slide imaging data with molecular and clinical data sources\n Build scalable, production-quality machine learning workflows and pipelines using cloud infrastructure (AWS)\n Apply modern machine learning techniques including convolutional neural networks (CNNs), vision transformers (ViTs), sequence transformers, representation learning, and foundation model fine-tuning\n Collaborate across technical and clinical teams to translate machine learning prototypes into validated tools\n Analyze model outputs to generate reproducible biological and clinical insights\n Document pipelines thoroughly and communicate data-driven findings clearly to cross-functional stakeholders\n \n QUALIFICATIONS: \n \n PhD in Computer Science, Computational Biology, Biomedical Engineering, Bioinformatics, Statistics, or a related quantitative discipline with a focus on machine learning or AI\n Core experience developing machine learning models for biomedical applications, specifically in medical imaging, computational pathology, genomics, transcriptomics, multi-omics, or molecular diagnostics\n Hands-on expertise with PyTorch and strong production-level programming skills in Python\n Practical application of deep learning architectures such as CNNs, transformers, attention mechanisms, and representation learning\n Experience managing datasets and training workflows within distributed or cloud computing environments (AWS)\n Proven ability to take ownership of research projects and translate prototypes into robust, deployment-ready workflows\n Experience adapting pre-trained foundation models for downstream biomedical applications\n \n PREFERRED QUALIFICATIONS: \n \n Experience integrating imaging, molecular, and clinical data within unified multimodal machine learning frameworks\n Technical familiarity with DNA sequencing, RNA sequencing, methylation, and ctDNA assays\n Hands-on experience with digital pathology software and whole-slide imaging analysis\n Exposure to survival modeling, longitudinal prediction, or time-to-event modeling\n Experience applying self-supervised learning, weakly supervised learning, or multiple instance learning (MIL) to clinical data\n Domain knowledge in oncology, biomarker discovery, or clinical precision medicine\n Track record of peer-reviewed publications in machine learning or computational biology conferences and journals (e.g., NeurIPS, ICML, CVPR, MICCAI, Nature Biomedical Engineering)\n \n #LI-DNI\n  \n The pay range is listed and actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years \u0026 depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations.\n Remote USA\n $124,800 — $156,000 USD \n OUR OPPORTUNITY \n Natera™ is a global leader in cell-free DNA (cfDNA) testing, dedicated to oncology, women’s health, and organ health. Our aim is to make personalized genetic testing and diagnostics part of the standard of care to protect health and enable earlier and more targeted interventions that lead to longer, healthier lives.\n The Natera team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists, business professionals, software engineers and many other professionals from world-class institutions, who care deeply for our work and each other. When you join Natera, you’ll work hard and grow quickly. Working alongside the elite of the industry, you’ll be stretched and challenged, and take pride in being part of a company that is changing the landscape of genetic disease management.\n WHAT WE OFFER \n Competitive Benefits - Employee benefits include comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents. Additionally, Natera employees and their immediate families receive free testing in addition to fertility care benefits. Other benefits include pregnancy and baby bonding leave, 401k benefits, commuter benefits and much more. We also offer a generous employee referral program!\n For more informatio","salary_min":124800,"salary_max":156000,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"mid","tags":["deep-learning","pytorch","healthcare","fine-tuning","generative-ai","cloud","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/natera/jobs/6004385004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T18:47:01Z","expires_at":"2026-06-29T14:10:20.275908Z","created_at":"2026-05-29T14:38:23.474911Z","updated_at":"2026-05-30T14:10:20.386097Z","company_name":"Natera","company_slug":"natera","company_logo_url":"https://www.google.com/s2/favicons?domain=natera.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/152a9a3c-a62a-4f20-a505-60c62517b468"},{"id":"31d8f599-c440-4857-a6e7-1da4b19cf92b","company_id":"654d4532-88db-435d-8a6f-161b8c5a491e","title":"Senior Manager, Data Science - Styling Algorithms","slug":"senior-manager-data-science-styling-algorithms-de952706","description":"About Stitch Fix, Inc. \n Stitch Fix (NASDAQ: SFIX) Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we’re equally committed to building yours.  We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what’s possible for our clients, while we help you reach your full potential.\n About the Role \n At Stitch Fix, we are at the forefront of innovation, creating cutting-edge solutions that blend fashion, technology, and data science. Our data science team combines machine learning with expert human judgment to generate innovative recommendations and insights that transform the way our clients discover what they love. We believe in a curiosity-driven data science culture where members are empowered to deliver impact through end-to-end model development. The diversity of the problems that we work on and the data-rich environment of our business make it possible, even essential, to bring the tools of multiple disciplines to bear on our hardest problems.  \n We are looking for an experienced Styling Algorithms Team Manager to lead a group of talented machine learning engineers and data scientists. In this role, you will shape the future of fashion technology by driving the development and deployment of our styling algorithms, which empower our human stylists to delight clients by nailing their fit and style. This includes ML-, AI-, and product-driven feature curation and testing for our proprietary styling platform, as well as client-facing AI personalization experiences, such as Stitch Fix Vision, our virtual try-on.\n Responsibilities: \n \n Champion bold AI and ML interventions to improve our styling experiences, enabling our stylists to have a multiplicative impact on their client connection points.\n Likewise, actively shape the product roadmap for direct client-facing styling experiences, expanding the breadth and depth of personalization touchpoints to complement and inform our human stylists.\n Inspire your team by fostering a culture of ideation, ownership, feedback, and collaboration between team members and with cross-functional partners.\n Act as an advocate for our Styling and Merchandising teams, empowering partners to understand trends in stylist feedback and inventory surfacing algorithms for rapid action on emergent opportunities. \n Work with product managers, other data science teams, UI/UX designers, and business leaders to define and optimize against business objectives for our suite of styling experiences.\n Oversee the end-to-end algorithm development lifecycle, from ideation and experimentation to testing and deployment in a production environment.\n Identify and implement best practices for team collaboration, code quality, use of AI, and data management.\n Stay up-to-date with advancements in AI-assisted development, AI-enabled product experiences, machine learning, and fashion technology.\n \n About You \n This is what you’ll need to succeed in this role from day 1. \n Requirements: \n \n Bachelor’s Degree in a quantitative field such as Computer Science, Statistics, Physics, Mathematics, or a related field required. Master’s or PhD preferred. \n 5+ years of experience in design and deployment of AI and ML solutions, ideally in retail personalization, with an emphasis on agentic capabilities.\n 2+ years of experience as a team technical lead or direct people manager.\n Ability to write and review production-grade code, ideally in Python.\n Applied knowledge of AI-assisted coding best practices and development of agentic product solutions.\n Excels at building trust with your team, stakeholders, and technical partners.\n Excellent communication skills with the ability to articulate complex technical concepts to business audiences.\n Experience with online A/B testing, experimentation frameworks, and performance metrics.\n Familiar with cloud-based infrastructure and distributed data systems.\n Compensation and Benefits This role will receive a competitive salary, benefits, and equity. The salary for US-based employees hired into this role will be aligned with the range below, which includes our three geographic areas. A variety of factors are considered when determining someone’s compensation–including a candidate’s professional background, experience, location, and performance. This position is eligible for an annual bonus, and new hire and ongoing grants of restricted stock units, depending on employee and company performance. In addition, the position is eligible for medical, dental, vision, and other benefits. Applicants should apply via our internal or external careers site. \n Salary Range\n $200,000 — $246,000 USD \n This link leads to the machine readable files that are made available in response to the federal Transparency in Coverage Rule and includes negotiated service rates and out-of-network allowed amounts","salary_min":200000,"salary_max":246000,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["healthcare","generative-ai","agents","payments","data-science"],"apply_url":"https://www.stitchfix.com/careers/jobs?gh_jid=7954690\u0026gh_jid=7954690","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T15:16:09Z","expires_at":"2026-06-29T14:18:30.876264Z","created_at":"2026-05-29T15:09:51.374959Z","updated_at":"2026-05-30T14:18:30.987883Z","company_name":"Stitch Fix","company_slug":"stitch-fix","company_logo_url":"https://www.google.com/s2/favicons?domain=stitchfix.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/31d8f599-c440-4857-a6e7-1da4b19cf92b"},{"id":"d8372e30-6a66-49c1-b225-3271b0a4a19f","company_id":"a4de8095-cb98-4b8b-9bfc-c2d248f257ea","title":"Senior Staff Security Engineer, AI","slug":"senior-staff-security-engineer-ai-5fc21c61","description":"At Ripple, we’re building a world where value moves like information does today. It’s big, it’s bold, and we’re already doing it. Through our crypto solutions for financial institutions, businesses, governments and developers, we are improving the global financial system and creating greater economic fairness and opportunity for more people, in more places around the world. And we get to do the best work of our career and grow our skills surrounded by colleagues who have our backs.  \n If you’re ready to see your impact and unlock incredible career growth opportunities, join us, and build real world value. \n \n THE WORK: \n As a Senior Staff Security Engineer focused on AI Security, you will be Ripple's deepest technical expert at the intersection of artificial intelligence and security. This is a purpose-built, high-impact individual contributor role that spans two critical mandates: securing AI systems that Ripple builds and operates, and harnessing AI to make Ripple's security function faster, smarter, and more scalable.\n You will lead the technical strategy for AI security across the agentic SDLC, define and operationalize guardrails for LLM and agentic AI adoption, and build AI-powered security tooling in close partnership with the broader organization to embed AI security into how Ripple operates every day. You will also shape Ripple's external posture on AI security, contributing to industry standards, regulatory discussions, and Ripple's published security practices.\n WHAT YOU’LL DO: \n \n Drive the AI Security technical strategy and roadmap, defining how Ripple secures its AI systems, governs agentic workflows, and embeds security controls into the AI development lifecycle from day one.\n Design and implement security controls for LLM-integrated and agentic AI systems, including sandboxing, identity and permission scoping, runtime monitoring, and containment of autonomous agent actions that exceed authorized scope.\n Own AI security across the Controlled Agentic SDLC, establishing security guardrails, AI provenance standards, dual-review requirements, and audit trail controls for AI-assisted development across Ripple Engineering.\n Lead the security review and risk assessment of all AI integrations entering production, including LLM APIs, SaaS copilots, AI code editors, agentic workflows, third-party MCP servers, and vendor-embedded AI.\n Build and scale Ripple's Shadow AI detection capability, surfacing unsanctioned AI usage, driving adoption of the AI acceptable use policy, and ensuring all AI workflows operate within Ripple's auditable perimeter.\n Serve as Ripple's go-to technical resource on agentic AI risks, including MCP server security, tool poisoning, prompt injection at the orchestration layer, and excessive agency in multi-agent systems, translating emerging threats into concrete mitigations with Engineering and Product.\n Shape Ripple's external AI security posture, contributing to industry frameworks, engaging regulators, and publishing research that establishes Ripple as a credible voice in responsible AI security. \n \n \n WHAT YOU'LL BRING:  \n \n \n 10+ years of Security Engineering experience with demonstrated depth in at least two domains, such as Product Security, Cloud Security, or Security Operations, and meaningful hands-on exposure to AI or ML security in practice.\n Solid understanding of AI and LLM security concepts, including prompt injection, jailbreaks, data poisoning, model extraction, RAG manipulation, and agentic risks such as tool poisoning, excessive agency, and MCP server vulnerabilities.\n Experience securing agentic AI systems, including sandboxing, permission scoping, human-in-the-loop design, or runtime monitoring for autonomous workflows.\n Fluency with core Security Engineering domains including cloud security on AWS, GCP, or Azure, CI/CD pipeline security, container and Kubernetes security, IAM, and API security, with the ability to reason about how these apply in AI-specific contexts.\n Strong threat modeling instincts, whether using STRIDE, MITRE ATLAS, OWASP LLM Top 10, or your own approach, and comfort applying frameworks to architectures where the playbook remains in development.\n Experience in FinTech, crypto, or other highly regulated environments is a strong plus, ideally with exposure to frameworks like NYDFS, MAS, DORA, or SOC 2 as they relate to AI adoption.\n Proven ability to work across teams, influence technical direction without direct authority, and bring structure to problems that span Engineering, Product, and Security.\n A genuine builder's mentality. You are energized by problems without established playbooks, comfortable building in ambiguity, and motivated by raising the bar in an area that is still being defined.\n \n Other common names for this role: AI Security Architect, LLM Security Engineer, Agentic AI Security Lead \n For positions that will be based in CA, the annual salary range for this position is below. Actual salaries may vary based","salary_min":232000,"salary_max":290000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["llm","healthcare","payments","rag","code-generation","agents","security"],"apply_url":"https://ripple.com/careers/all-jobs/job/7961902?gh_jid=7961902","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T13:13:15Z","expires_at":"2026-06-29T14:12:02.752999Z","created_at":"2026-05-28T14:13:53.327797Z","updated_at":"2026-05-30T14:12:02.874002Z","company_name":"Ripple","company_slug":"ripple","company_logo_url":"https://www.google.com/s2/favicons?domain=ripple.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d8372e30-6a66-49c1-b225-3271b0a4a19f"},{"id":"afcbd32a-2f1d-4a75-9315-8bcd1e76ad5e","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Staff Machine Learning Engineer, Fulfillment Planning","slug":"staff-machine-learning-engineer-fulfillment-planning-8c6dac71","description":"About the Team \n The Fulfillment Planning team builds the intelligence that powers DoorDash’s logistics network. We optimize how deliveries are planned and executed across the full delivery lifecycle, improving customer experience, merchant outcomes, Dasher efficiency, and DoorDash profitability.  Our mission is to improve fulfillment quality while reducing fulfillment cost. We do this by applying machine learning, optimization, and systems engineering to the core decisions behind assignment, routing, batching, timing, and fulfillment estimation.\n The team works on some of DoorDash’s most important logistics systems, including:\n \n The core assignment engine that matches deliveries with Dashers in real time.\n Real-time ETA and fulfillment estimation systems for consumers, Dashers, and merchants across diverse geographies and all business lines.\n Assignment and planning algorithms for specialized delivery types, including grocery, retail, parcel, and catering.\n ML models and optimization algorithms that shape demand, improve service quality, and reduce cost.\n Tier-0 logistics services that require high reliability, low latency, and strong operational discipline.\n \n The team also builds reusable ML systems and modeling patterns that scale across DoorDash’s logistics ecosystem. This role will help define the technical direction and best practices for logistics ML at DoorDash.\n About the Role \n We’re looking for a Staff Machine Learning Engineer to lead the design, development, and deployment of large-scale production ML systems that drive real-time decisioning across DoorDash’s fulfillment ecosystem.\n You will start by owning ML systems for assignment and fulfillment estimation, partnering closely with Product, Data Science, Engineering, and Platform teams to improve delivery quality, cost, and efficiency. Over time, you may also contribute to adjacent areas such as batching, fulfillment execution, demand shaping, and logistics optimization across DoorDash’s business lines.\n This is a high-impact individual contributor role for someone who enjoys building 0→1 ML systems, operating at Staff-level scope, and influencing technical direction across multiple teams. You will define architectures, set modeling and deployment standards, mentor other engineers, and help shape how DoorDash applies machine learning to logistics at scale.\n You’re excited about this opportunity because you will… \n \n Own and build foundational ML systems that directly impact delivery quality, cost, and overall logistics efficiency across DoorDash.\n Work on challenging, real-world machine learning problems , including real-time assignment, routing, and fulfillment estimation.\n Lead 0→1 ML initiatives , defining how machine learning and optimization are applied across fulfillment products.\n Influence architecture, strategy, and execution for a Tier-0 service critical to DoorDash’s logistics platform.\n Collaborate closely with Product, Data Science, and Platform Engineering in a highly cross-functional environment.\n Establish best practices for model development, deployment, monitoring, retraining, and governance.\n Define and lead DoorDash’s cutting-edge AI vision for logistics: an LLM-inspired foundation model for intelligence across logistics\n Mentor other engineers and raise the technical bar for logistics ML across the organization.\n \n We’re excited about you because… \n \n You have 8+ years of industry experience building and deploying production-scale machine learning systems.\n You have strong machine learning fundamentals and know how to apply them to large-scale production systems.\n You are fluent in Python\n You have hands-on experience with modern ML frameworks, especially deep learning frameworks.\n You have designed, launched, and operated mission-critical ML models or systems in production, including monitoring, retraining, reliability, and governance.\n You can lead complex technical projects end to end and influence stakeholders across multiple teams or organizations.\n You communicate clearly with both technical and non-technical audiences.\n You are comfortable operating in ambiguous problem spaces and turning 0→1 ideas into production systems.\n You have built or shipped large-scale ML models for recommendation, ads, marketplace, logistics, or other domains.\n You have experience with knowledge distillation from large teacher models into efficient production models.\n \n  \n Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only\n We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.\n The Covey tool has been reviewed ","salary_min":203500,"salary_max":299300,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["llm","fine-tuning","generative-ai","cloud","healthcare","deep-learning","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/7962110","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-27T23:47:57Z","expires_at":"2026-06-29T14:18:34.57356Z","created_at":"2026-05-28T14:20:10.032116Z","updated_at":"2026-05-30T14:18:34.681457Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/afcbd32a-2f1d-4a75-9315-8bcd1e76ad5e"},{"id":"79fa1bbf-4677-4dd1-b934-83c129fa9aef","company_id":"9d70a126-16ff-4f5c-9f36-2133735865d3","title":"Engineering Manager, Agentic Workflows ","slug":"engineering-manager-agentic-workflows-ee84264f","description":"Who We Are \n Verkada is transforming how organizations protect their people and places with an integrated, privacy-sensitive AI-powered platform that includes solutions for video security, access control, air quality sensors, alarms, intercoms, and visitor management. \n We’ve got serious momentum in the market: more than 30,000 customers (including 100+ of the Fortune 500), a $5.8B valuation , more than $1 billion in annualized bookings, and backing from CapitalG, Sequoia Capital, General Catalyst, Felicis Ventures, Next47 and more. Physical AI is one of the most consequential technology shifts of our time, and Verkada is at the center of it.\n You can look at all kinds of communities to see our platform’s impact in the world. It's the retailer that uses our agentic AI to deter theft before it happens. The warehouse that uses AI-powered alerts to make sure its team is protected on the floor with proper PPE. The school that’s alerted to a threat in real-time and triggers a lockdown in seconds, not minutes. We’re rapidly scaling this impact: today, more than 2 million Verkada devices are deployed across 170+ countries. \n \n About the Role \n We are looking for an Engineering Manager to lead a new team focused on building AI agents that improve engineering velocity, reliability, and developer experience across the company. This team will operate with a 0→1 charter inside our Infrastructure / DevX organization, developing agentic systems that automate workflows such as CI failure triage, autonomous deployments, incident response, and proactive bug detection. The work will have a broad impact across all engineering teams by reducing toil and enabling faster iteration.\n This role is both strategic and hands-on: you will define the roadmap, build and grow the team, and actively contribute to prototyping and development.\n What You'll Do \n \n Make every engineer more productive by eliminating repetitive workflows through AI agents\n Define and own the agent roadmap: what to automate, in what order, and how to measure success\n Build and lead a small, high-impact team of engineers\n Contribute hands-on to prototyping, coding, and unblocking technical challenges\n Establish evaluation frameworks for agent performance (golden tasks, regression sets, replay, LLM-as-judge)\n Partner closely with Infrastructure, Security, and DevX teams to integrate agents into core workflows\n Drive high engineering standards through design docs, RFCs, and strong execution\n \n What You Bring \n \n 7+ years of software engineering experience, with 2+ years in engineering management\n Proven experience shipping production systems, including agentic or automation-heavy workflows\n Strong hands-on coding ability in Python, Go, or TypeScript\n Experience building systems that interact with APIs, tools, and external services (not just prompt-based interfaces)\n Demonstrated ability to define metrics and evaluate system performance rigorously\n Experience writing clear technical design documents and driving alignment\n \n Nice to Have \n \n Experience building or managing developer tooling or internal platforms\n Familiarity with agent frameworks or orchestration systems\n Experience in monorepo environments\n Startup or early-stage team experience (0→1 or small team scaling)\n \n \n US Employee Benefits \n Verkada is committed to fostering a workplace environment that prioritizes the holistic health and wellbeing of our employees and their families by offering comprehensive wellness perks, benefits, and resources. Our benefits and perks programs include, but are not limited to:\n \n Healthcare programs that can be tailored to meet the personal health and financial well-being needs - Premiums are 100% covered for the employee under at least one plan and 80% for family premiums under all plans\n Nationwide medical, vision and dental coverage\n Health Saving Account (HSA) with annual employer contributions and Flexible Spending Account (FSA) with tax saving options\n Expanded mental health support\n Paid parental leave policy \u0026 fertility benefits\n Time off to relax and recharge through our paid holidays, firmwide extended holidays, flexible PTO and personal sick time\n Professional development stipend\n Fertility Stipend\n Wellness/fitness benefits\n Healthy lunches provided daily\n Commuter benefits\n \n Additional Information \n \n We do sponsor and take over sponsorship of employment visas for this role. If we make you an offer, we will make every reasonable effort to get you a visa.\n \n Annual Pay Range \n At Verkada, we want to attract and retain the best employees, and compensate them in a way that appropriately and fairly values their individual contribution to the company. With that in mind, we carefully consider a number of factors to determine the appropriate starting pay for an employee, including their primary work location and an assessment of a candidate's skills and experience, as well as market demands and internal parity. A Verkada employee may be eligible for ","salary_min":200000,"salary_max":350000,"location":"San Mateo, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["agents","llm","healthcare","infrastructure"],"apply_url":"https://job-boards.greenhouse.io/verkada/jobs/5148388007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-27T23:10:47Z","expires_at":"2026-06-29T14:09:29.112725Z","created_at":"2026-05-28T14:11:05.261963Z","updated_at":"2026-05-30T14:09:29.226552Z","company_name":"Verkada","company_slug":"verkada","company_logo_url":"https://www.google.com/s2/favicons?domain=verkada.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/79fa1bbf-4677-4dd1-b934-83c129fa9aef"},{"id":"2f82717a-ca5c-44ec-afbc-871db9888784","company_id":"f36ec848-cb19-4b95-a680-6733e58086c0","title":"Director, Data Science","slug":"director-data-science-e0c2bfe0","description":"May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. Based in Ann Arbor, Michigan, May develops and deploys autonomous vehicles (AVs) powered by our innovative Multi-Policy Decision Making (MPDM) technology that literally reimagines the way AVs think. Our vehicles do more than just drive themselves - they provide value to communities, bridge public transit gaps and move people where they need to go safely, easily and with a lot more fun. We’re building the world’s best autonomy system to reimagine transit by minimizing congestion, expanding access and encouraging better land use in order to foster more green, vibrant and livable spaces. Since our founding in 2017, we’ve given more than 500,000 autonomous rides to real people around the globe. And we’re just getting started. We’re hiring people who share our passion for building the future, today, solving real-world problems and seeing the impact of their work. Join us. \n Job Summary \n May Mobility is entering an exciting phase of growth as we expand our autonomous transit and mobility services across the country. Founded in 2017 by a team of experienced roboticists, perception, behavior, AI, and software engineers, we operate driverless transit shuttles in real communities — not as a research demonstration, but as a daily-service product that people rely on to get to work, school, and home.\n The Director, Data Science will lead the team responsible for turning the data generated by our fleet, simulation environment, and ML systems into the insights, evaluations, and decisions that make our autonomous service safer, more efficient, and ready to scale into new cities. You will own data science across simulation and synthetic data, perception and planning ML evaluation, fleet operations analytics, and the data infrastructure that supports them. You will partner directly with Engineering, Product, Operations, and Safety leadership to set measurement standards, define release criteria, and translate frontline operating data into the next generation of our autonomy stack.\n This is a leadership role for someone who has scaled a data science function inside a hard-tech environment, who is comfortable making engineering and product tradeoffs alongside their team, and who sees the gap between research-grade ML and production transit-grade ML as the most interesting problem in the industry today.\n Essential Responsibilities \n \n Set and own the data science strategy across simulation and synthetic data, ML evaluation (perception, prediction, planning), fleet operations analytics, and the data platform that supports them; translate that strategy into a 12–24 month roadmap with measurable milestones.\n Lead, grow, and develop a team of senior data scientists, ML engineers, and front-line managers; recruit from a small expert pool, calibrate the bar, and build a hiring brand that allows May Mobility to win against AV, robotics, and AI competitors.\n Partner with Engineering, Product, Safety, and Operations leaders to define release criteria, performance metrics, and ODD-expansion gates; use data to make the business case for what we deploy, where, and when.\n Drive ML and analytics applications end-to-end: dataset curation, scenario coverage, modeling, offboard evaluation, productionization, and continuous monitoring of fleet performance in the wild.\n Establish measurement and experimentation standards across the company — including before/after analyses for stack changes, A/B-style comparisons in simulation, and statistically credible reporting on real-world incidents.\n Lead team-wide quality activities including design and code reviews; hold the bar on engineering rigor for production data science systems.\n Track and trend technical performance of the autonomy stack in the field; surface root causes, prioritize fixes with engineering, and represent fleet-data findings to executives, regulators, and partners.\n Provide technical guidance to Engineering and Operations leaders on issue diagnosis, resolution, and the ML changes most likely to move our key safety and service metrics.\n Represent May Mobility's data science work externally where appropriate — through publications, conference talks, partner reviews, and recruiting.\n \n Skills and Abilities \n Success in this role typically requires the following competencies: \n \n Autonomy Data Expertise. Can reason fluently about the data produced by a modern AV stack — sensor logs, perception outputs, planning traces, simulator results, and operational telemetry — and can identify which signals matter for which decisions.\n Hands-On Technical Depth. Has personally shipped production ML or analytics systems within the last 3–5 years and is credible in code review and design review with senior engineers and scientists.\n Cross-Functional Translator. Can explain a complex ML or statistical finding to engineering, product, and executive audiences; and ","salary_min":217000,"salary_max":312000,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"lead","tags":["robotics","healthcare","distributed-systems","pytorch","computer-vision","tensorflow","reinforcement-learning","autonomous-vehicles"],"apply_url":"https://job-boards.greenhouse.io/maymobility/jobs/8561428002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-27T21:54:47Z","expires_at":"2026-06-29T14:17:06.3175Z","created_at":"2026-05-28T14:18:43.046233Z","updated_at":"2026-05-30T14:17:06.431533Z","company_name":"May Mobility","company_slug":"may-mobility","company_logo_url":"https://www.google.com/s2/favicons?domain=maymobility.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/2f82717a-ca5c-44ec-afbc-871db9888784"},{"id":"dc3be083-3d88-4196-ae36-689fe5f1b3fe","company_id":"654d4532-88db-435d-8a6f-161b8c5a491e","title":"Senior Manager, Data Science - Foundational Models","slug":"senior-manager-data-science-ee646aa7","description":"About Stitch Fix, Inc. \n Stitch Fix (NASDAQ: SFIX) Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we’re equally committed to building yours.  We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what’s possible for our clients, while we help you reach your full potential.\n  \n About the Role \n At Stitch Fix, we are at the forefront of innovation, creating cutting-edge solutions that blend fashion, technology, and data science. Our data science team combines machine learning with expert human judgment to generate innovative recommendations and insights that transform the way our clients discover what they love. We believe in a curiosity-driven data science culture where members are empowered to deliver impact through end-to-end model development. The diversity of the problems that we work on and the data-rich environment of our business make it possible, even essential, to bring the tools of multiple disciplines to bear on our hardest problems.  \n We are looking for an experienced Foundational Models Team Manager to lead a group of talented machine learning engineers and data scientists. In this role, you will shape the future of fashion technology by driving the development and deployment of our core scoring and ranking algorithms. These industry-leading machine learning models match clients to available inventory, supporting our stylists in designing Fixes and powering online personalization directly to our clients.\n Responsibilities: \n \n Champion cutting-edge machine learning and AI techniques to improve holistic client engagement, personalization, and overall growth.\n Represent our core algorithmic capabilities in cross-functional forums, including with our executive leadership team, synthesizing business requirements and translating technical solutions with radical transparency and a solution-oriented mindset.\n Lead and inspire a team building transformative capabilities at the heart of our company’s value proposition, synthesizing and balancing multiple business objectives.\n Foster a culture of ownership for holistic business outcomes within the team, encouraging proactive engagement with cross-functional partners.\n Drive the development and optimization of our prediction and recommendation algorithms, ensuring they provide personalized, relevant, and engaging fashion recommendations for stylists and clients.\n Oversee the end-to-end algorithm development lifecycle—from ideation and experimentation to testing and deployment in a production environment.\n Manage the prioritization and execution of key algorithmic projects while balancing business needs, technical feasibility, and timelines.\n Implement industry best practices for team collaboration, code quality, use of AI, and data management.\n Stay up-to-date with the latest trends and advancements in AI-assisted development, AI-enabled product experiences, machine learning, and fashion technology.\n \n About You \n This is what you’ll need to succeed in this role from day 1. \n Requirements: \n \n Bachelor’s Degree in a quantitative field such as Computer Science, Statistics, Physics, Mathematics, or a related field required. Master’s or PhD preferred. \n 5+ years of experience in design and deployment of machine learning algorithms, ideally in retail applications of deep learning and recommendation systems.\n 2+ years of experience in a direct people management role, with a track record of inspiring and motivating direct reports, and connecting team priorities to business objectives.\n Ability to write and review production-grade code, ideally in Python.\n Applied knowledge of AI-assisted coding best practices and development of agentic product solutions.\n Excels at building trust with your team, stakeholders, and technical partners.\n Excellent communication skills with the ability to articulate complex technical concepts to non-technical audiences.\n Experience with online A/B testing, experimentation frameworks, and performance metrics.\n Familiar with cloud-based infrastructure and distributed data systems.\n Compensation and Benefits This role will receive a competitive salary, benefits, and equity. The salary for US-based employees hired into this role will be aligned with the range below, which includes our three geographic areas. A variety of factors are considered when determining someone’s compensation–including a candidate’s professional background, experience, location, and performance. This position is eligible for an annual bonus, and new hire and ongoing grants of restricted stock units, depending on employee and company performance. In addition, the position is eligible for medical, dental, vision, and other benefits. Applicants should apply via our internal or external careers site. \n Salary Range\n $200,000 — $246,000 USD \n This link leads t","salary_min":200000,"salary_max":246000,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["deep-learning","healthcare","agents","generative-ai","payments","data-science"],"apply_url":"https://www.stitchfix.com/careers/jobs?gh_jid=7947680\u0026gh_jid=7947680","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-27T19:21:44Z","expires_at":"2026-06-29T14:18:30.789303Z","created_at":"2026-05-28T14:20:06.359409Z","updated_at":"2026-05-30T14:18:30.909247Z","company_name":"Stitch Fix","company_slug":"stitch-fix","company_logo_url":"https://www.google.com/s2/favicons?domain=stitchfix.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/dc3be083-3d88-4196-ae36-689fe5f1b3fe"},{"id":"fde598de-15bc-4dbe-bde8-a8635779a8bd","company_id":"776e5e7d-beba-4889-a481-6d9d7c3af325","title":"Engineering Manager, Agents","slug":"engineering-manager-agents-ba9a26b5","description":"About Decagon\n\nDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.\n\nOur technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.\n\nWe’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.\n\nWe’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.\n\n\n\nAbout the Team\n\nThe Agent Engineering team at Decagon deploys mission-critical AI agents to our customers that impact millions of users and directly drive Decagon’s growth. You will lead a team building on our industry-leading AI agent platform, collaborate directly with customers and help devise long-term, scalable solutions.\n\nOur mission is to deliver magical support experiences — AI agents working alongside human agents to help users resolve their issues.\n\n\nAbout the Role\n\nAs an Engineering Manager on the Agent Engineering team, you’ll lead a group of engineers building and shipping best-in-class AI agents, from initial implementation through continuous iteration. You’ll work directly with leaders across industries like finance, healthcare and hospitality, solving their users’ needs with reliable and intuitive AI agents.\n\nManagers here are expected to operate with high ownership and technical depth while helping their teams move quickly and maintain a high quality bar. This role is for someone who enjoys mentoring engineers, partnering closely with customers and diving deep into complex system challenges to build elegant solutions that scale to millions of users.\n\n\nIn this role, you will\n\n - Lead and grow a team of engineers building AI agents that outperform human agents in managing complex customer interactions and driving customer retention\n\n - Partner directly with enterprise customers to understand their operational pain points and translate them into scalable AI agent solutions\n\n - Drive execution across the full lifecycle of agent deployments, from initial implementation through continuous iteration and optimization\n\n - Partner with product, design and research to identify cross-customer trends that guide the evolution of Decagon’s agent platform and research efforts\n\n - Help define the technical strategy and roadmap for the future of AI-powered customer support\n\n - Support and mentor engineers through technical guidance, feedback and career development\n\n - Maintain a high engineering bar while fostering a culture of ownership, velocity and customer obsession\n   \n\nYour background looks something like this\n\n - Have 1+ years of engineering management experience\n\n - Have 5+ years of industry experience in software engineering\n\n - Proficiency with Python, Typescript and asynchronous programming\n\n - Experience leading teams building complex distributed systems or customer-facing products\n\n - A high degree of comfort digging into system failures within deep technology stacks using any tool necessary\n\n - Strong communication skills and ability to work directly with enterprise customers\n   \n\nEven better\n\n - Prior experience working with multi-modal models\n\n - Experience leading teams working on AI systems, LLM applications or agentic workflows\n\n\n\nCompensation\n\n$200K – $400K + Offers Equity\n\nThis range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and the scope of responsibilities, with flexibility for candidates who demonstrate exceptional impact.\n\nIn addition to base salary, we offer competitive equity. Final compensation may vary based on location within the United States.\n\n\n\nBenefits\n\nWe proudly offer the following benefits for our full-time employees:\n\n - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)\n\n - Medical, Dental, and Vision benefits for you and your family\n\n - Life Insurance and Disability Benefits\n\n - Retirement Plan (e.g., 401K, pension)\n\n - Parental Leave\n\n - Fertility and family building benefits through Carrot\n\n - Daily lunches and snacks in the office to keep you at your best\n\nThese benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.","salary_min":200000,"salary_max":400000,"location":"New York, NY","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["agents","distributed-systems","llm","healthcare"],"apply_url":"https://jobs.ashbyhq.com/decagon/0902f176-33a3-4233-be8a-1e22d1e8d23d/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-27T18:38:19.97Z","expires_at":"2026-06-29T14:07:13.313017Z","created_at":"2026-05-28T14:08:44.791187Z","updated_at":"2026-05-30T14:07:13.432945Z","company_name":"Decagon","company_slug":"decagon","company_logo_url":"https://www.google.com/s2/favicons?domain=decagon.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/fde598de-15bc-4dbe-bde8-a8635779a8bd"},{"id":"0ffaba88-636c-40f6-b308-69d1b07a2471","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Senior Platform AI Engineer","slug":"senior-platform-ai-engineer-4ad89166","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata's AI Platform team builds the production infrastructure that powers AI features across our compliance platform — from MCP servers that make Drata's data available to AI agents, to LLM workflow orchestration that automates SOC 2, TPRM, and policy analysis. You'll own the systems that sit between our AI models and our customers: tool definitions that agents actually understand, deployment pipelines that handle model upgrades without breaking output quality, and orchestration layers that manage multi-step agent workflows with persistent state.\n\nThis is not a traditional infrastructure role. You'll debug prompt templates alongside Terraform modules. You'll design API schemas optimized for LLM token budgets, not just HTTP throughput. When a model upgrade changes behavior across 15 workflows, you'll assess quality impact — not just confirm the containers are healthy.\n\nYou'll work closely with our agent developers, product engineers, and an embedded SRE partner, sitting at the intersection of AI development and production reliability.\n\nOur north star is simple: minimize the time it takes to launch a new agent in production. You're someone who asks \"are we solving the right problem?\" before writing the first line of code, who builds systems that make five other engineers faster, not just yourself, and who's equally proud of what they chose not to build.\n\nWhat you'll do:\n\n\nMCP SERVER DEVELOPMENT \u0026 AI-OPTIMIZED API DESIGN\n\n - Design and build MCP (Model Context Protocol) servers that expose Drata's platform to AI agents. This means making architectural decisions about tool granularity, naming conventions for agent disambiguation, response compression for LLM context windows, and workspace isolation for multi-tenant access. You'll own the protocol layer that determines whether agents can reliably find and use the right tools — writing semantic parameter descriptions, contextual hints, and tool schemas that optimize for model comprehension, not just developer ergonomics.\n\n\nAGENT ORCHESTRATION \u0026 WORKFLOW INFRASTRUCTURE\n\n - Build and operate the infrastructure for deploying multi-step agent workflows — state management across complex reasoning chains, tool routing and execution runtimes, and long-running agentic processes that persist over time. Own the orchestration layer that coordinates agent planning, tool calls, and human-in-the-loop patterns. Design systems that handle agent failure modes gracefully: retries on ambiguous tool ","salary_min":192000,"salary_max":259800,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["distributed-systems","search","healthcare","llm","cloud","rag","agents","api-design"],"apply_url":"https://jobs.ashbyhq.com/drata/f0ab62fb-c0a8-4bf2-bfd6-9d9d2e68fb91/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T23:02:26.469Z","expires_at":"2026-06-29T14:13:56.372048Z","created_at":"2026-05-27T14:14:32.001255Z","updated_at":"2026-05-30T14:13:56.493566Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0ffaba88-636c-40f6-b308-69d1b07a2471"},{"id":"84366e11-6b70-4a34-a8c9-d03cd29bd00e","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Senior Applied Research Engineer","slug":"senior-applied-research-engineer-a868acf4","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata is seeking a Senior Applied Research Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research.\n\nThis is a research-focused role emphasizing experimentation and rigor over production engineering. You'll own the science behind how Drata's AI products retrieve, reason, and respond — and you'll work closely with AI and Software Engineers to turn validated approaches into production-ready systems.\n\nDrata's compliance platform is document-heavy: VRM Agent, AIQA, Trust Agent, policy-to-control mappers, and more all depend on high-quality information retrieval and reasoning.\n\nWhat you'll do:\n\n - Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, semantic routing\n\n - Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements ↔ evidence)\n\n - Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and structured prediction\n\n - Build and maintain evaluation frameworks: golden datasets, automated quality metrics, regression detection\n\n - Implement and tune ranking/reranking systems: cross-encoders, LLM-based rerankers, learning-to-rank, custom scoring functions\n\n - Run experiments to validate hypotheses and quantify improvements before production rollout\n\n - Debug failure modes and build error taxonomies across retrieval, reasoning, and generation\n\n - Collaborate with AI and Software Engineers to hand off validated approaches for productionization\n\n - Stay current on applied research in RAG, agents, LLM evaluation, and relevance modeling; bring innovations into the product\n\nWhat you'll bring:\n\n - 5+ years of experience in applied research, data science, or ML with a focus on NLP, information retrieval, or knowledge systems\n\n - 2+ years of hands-on experience building or contributing to production AI/ML systems\n\n - Strong foundation in information retrieval: dense and sparse retrieval, embedding models, search relevance\n\n - Experience with RAG systems: chunking strategies, vector databases, retrieval optimization\n\n - Proficiency in evaluation methodology: metrics design, golden dataset creation, A/B testing, statistical significance\n\n - Strong Python skills and comfort with notebook-driven research wo","salary_min":166900,"salary_max":225900,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["nlp","generative-ai","rag","embeddings","search","llm","agents","healthcare"],"apply_url":"https://jobs.ashbyhq.com/drata/fab401cd-087e-4b69-8a62-f0dbae4906c9/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T22:59:45.262Z","expires_at":"2026-06-29T14:13:57.168877Z","created_at":"2026-05-27T14:14:33.203504Z","updated_at":"2026-05-30T14:13:57.34909Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/84366e11-6b70-4a34-a8c9-d03cd29bd00e"},{"id":"5e52cfc4-669e-46bb-8b87-84c11248ba64","company_id":"72014eb6-e84d-48c2-af5c-5424ebec0b3c","title":"Analytics Engineer","slug":"analytics-engineer-97634fa3","description":"Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com .\n Analytics Engineer - Consumer Data Science \n Check out our r/RedditEng post to learn more about the team, and what we do: https://www.reddit.com/r/RedditEng/comments/1mnmf71/analytics_engineering_reddit/  \n On Reddit, people can dive into anything through experiences built around their interests, hobbies, and passions. Our mission is to empower communities and make their knowledge accessible to everyone. With over 100,000 active communities and over 120 million daily active users, it is home to the most open and authentic conversations on the internet. Reddit’s unique and differentiated product is extremely attractive to advertisers, who can reach out to and connect to our users authentically.\n We are looking for a talented and driven individual to be a key part of our Analytics Engineering team within the Data Science organization, focused on the Consumer domain. We are looking for someone who can work closely with Data Scientists and members of Consumer cross-functional teams (Product, Engineering, and Design) to curate, develop, and deploy the right data and analytic tooling to drive Reddit’s product forward and provide a data and tooling foundation that will last decades. Your work will empower thousands of your colleagues to improve the user experience and grow our consumer base.\n Successful candidates have a strong track record of understanding and deeply caring about the purpose of data to support business goals, and can act as an effective conduit between Data Producers and Data Consumers. This role sits at the intersection of Data Science and Data Engineering, and the ideal candidate has skills, experience, and passion in both areas.\n Reddit has a flexible workforce! If you happen to live close to one of our physical office locations, our doors are open so you can come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence.\n Responsibilities: \n \n Be an Analytics Engineering leader within the Consumer organization and a key contributor and collaborator to the success of Data Science data quality, performance, reliability, and automation initiatives.\n Be the data steward for Consumer products: architect and improve the collection of underlying data while also creating ETLs, reporting dashboards, data aggregations and other deliverables needed for product feature tracking, user retention analysis, A/B testing, and a large number of other data-driven activities.\n Develop and maintain robust data pipelines and workflows for data ingestion, processing, and transformation. Work closely with engineering to ensure the quality and reliability of these data pipelines.\n Create user-friendly tools and applications for internal use across Data Science and cross-functional teams, streamlining data analysis and reporting processes. Drive widespread adoption of these tools and applications with a relentless focus on automation, consistency, and reliability.\n Lead transformational efforts to build a data-driven culture at Reddit by enabling data self-service.\n Provide technical guidance, mentorship, coaching and/or training to data scientists and other technical partners.\n Serve as a thought partner for data scientists, engineering managers, and leadership on data foundations, communicating and shaping the data foundations roadmap and strategy for Reddit.\n \n Qualifications: \n \n Degree in a quantitative discipline such as statistics, operations research, computer science, applied mathematics, economics, or physics\n 4+ years of experience working with large-scale ETL systems (implementation, strategy, and maintenance), building clean, maintainable code and systems (Python preferred) in a production environment.\n Strong programming proficiency in Python, SQL, Spark, Scala, etc.\n Experience with data modeling, ETL and ELT concepts, and patterns for efficient data governance. Experience with manipulating massive-scale structured and unstructured data.\n Experience with data workflows (such as Airflow), data modeling, front-end or back-end engineering.\n Experience in data visualization and dashboard design.\n Deep understanding of technical and functional designs for relational and MPP Databases.\n Proven track record of cross-functional execution and collaboration. Excellent communication skills to collaborate with cross-functional stakeholders at all levels of the company, of differing levels of technical acumen.\n Self-starter, ability to work independe","salary_min":164200,"salary_max":229900,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"lead","tags":["agents","healthcare","data-pipeline","data-science"],"apply_url":"https://job-boards.greenhouse.io/reddit/jobs/7958354","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T18:42:47Z","expires_at":"2026-06-29T14:08:29.565057Z","created_at":"2026-05-27T14:08:43.457817Z","updated_at":"2026-05-30T14:08:29.678303Z","company_name":"Reddit","company_slug":"reddit","company_logo_url":"https://www.google.com/s2/favicons?domain=www.reddit.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/5e52cfc4-669e-46bb-8b87-84c11248ba64"},{"id":"81e447ea-83f4-4966-a2c8-0a0512efef5b","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Senior AI Engineer, Agent Harness","slug":"senior-ai-engineer-agent-harness-1c6d9f8f","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata is advancing the frontier of compliance automation by integrating intelligent AI capabilities into its trust platform. We are seeking a Senior AI Engineer to help design, build, and scale robust, high-impact AI systems that improve operational efficiency, enhance decision-making, and support trust-critical enterprise workflows.\n\nThis role focuses on solving complex, real-world problems with agentic AI, LLMs, and intelligent reasoning systems in a compliance and security context.\n\nAs a Senior AI Engineer, you will own the end-to-end design, implementation, and evolution of AI-driven features across the Drata platform.\n\nWhat you'll do:\n\nBuild Agentic \u0026 Intelligent AI Systems\n\n - Design and implement LLM-powered systems capable of multi-step reasoning, evidence grounding, and decision support in high-stakes compliance environments\n\n - Develop agentic workflows that combine retrieval, tool use, structured reasoning, and human oversight\n\n - Create interactive AI experiences that allow users to engage naturally with complex compliance and risk data\n\nAutomated Reasoning Over Regulations \u0026 Evidence\n\n - Build AI systems that reason over structured and unstructured data to support regulatory interpretation, control validation, and risk assessment\n\n - Ensure AI outputs are traceable, explainable, and auditable, meeting the expectations of enterprise compliance teams\n\nProduction-Grade AI Architecture\n\n - Architect and deploy scalable LLM + retrieval + agent systems in production environments\n\n - Optimize for latency, cost, reliability, and evaluation in real-world enterprise workloads\n\n - Partner with platform, security, product teams, and other application development teams to operationalize AI safely and effectively\n\nResponsible \u0026 Trustworthy AI\n\n - Embed human-in-the-loop workflows, confidence thresholds, and safety guardrails into AI systems\n\n - Ensure privacy-preserving data handling, robust failure modes, and transparent behavior aligned with Drata's values\n\nWhat you'll bring:\n\n - Experience: 5+ years of hands-on software engineering experience; 2+ years specifically in ML/AI engineering\n\n - Programming Languages: Proficiency in Python; TypeScript experience is a plus, especially for production AI system integration\n\n - Retrieval \u0026 Vector Stores: Familiarity with vector databases (Pinecone, Chroma, FAISS, etc.) and RAG system design\n\n - LLM \u0026 AI Systems: Proven experience building and shipping LLM-based applications in production, i","salary_min":166900,"salary_max":225900,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["llm","agents","rag","healthcare","embeddings"],"apply_url":"https://jobs.ashbyhq.com/drata/374b4418-aa4c-4005-812e-76a450c61476/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:24:52.13Z","expires_at":"2026-06-29T14:13:56.699213Z","created_at":"2026-05-27T14:14:32.675788Z","updated_at":"2026-05-30T14:13:56.815439Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/81e447ea-83f4-4966-a2c8-0a0512efef5b"}],"page":1,"per_page":20,"total":1073,"total_pages":54}