{"has_next":true,"jobs":[{"id":"f8c6c621-b459-40f6-b41d-0baa191734ff","company_id":"a0000000-0000-0000-0000-000000000001","title":"Research Lead, Training Insights","slug":"research-lead-training-insights-6091f430","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 As a Research Lead on the Training Insights team, you'll develop the strategy for, and lead execution on, how we measure and characterize model capabilities across training and deployment. This is a hands-on leadership role: you'll drive original research into new evaluation methodologies while leading a small team of researchers and research engineers doing the same.\n Your work will span the full lifecycle of model development. You'll research and build new long-horizon evaluations that test the boundaries of what our models can achieve, develop novel approaches to measuring emerging capabilities, and deepen our understanding of how those capabilities develop — both during production RL training and after. You'll also take a cross-organizational view, working across Reinforcement Learning, Pretraining, Inference, Product, Alignment, Safeguards, and other teams to map the landscape of model evaluations at Anthropic and identify critical gaps in coverage.\n This role carries significant visibility and impact. You'll help shape the evaluation narrative for model releases, contributing directly to how Anthropic communicates about its models to both internal and external audiences. Done well, you will change how the industry measures and understands model capabilities, significantly furthering our safety mission.  \n Responsibilities:  \n \n Build new novel and long-horizon evaluations\n Develop novel measurement approaches for understanding how model capabilities emerge and evolve during RL training\n Lead strategic evaluation coverage across the company\n Shape the evaluation narrative for model releases\n Lead and mentor a small team of researchers and research engineers, setting research direction and fostering a culture of rigorous, creative research\n Design evaluation frameworks that balance scientific rigor with the practical demands of production training schedules\n Build and maintain relationships across Anthropic's research organization to ensure evaluation insights inform training and deployment decisions\n Contribute to the broader research community through publications, open-source contributions, or external engagement on evaluation best practices\n \n You may be a good fit if you:  \n \n Have significant experience designing and running evaluations for large language models or similar complex ML systems\n Have led technical projects or teams, either formally or through sustained ownership of critical research directions\n Are equally comfortable designing experiments and writing code—you can move between research and implementation fluidly\n Think strategically about what to measure and why, not just how to measure it\n Can synthesize information across multiple teams and workstreams to form a coherent picture of model capabilities\n Communicate complex technical findings clearly to both technical and non-technical audiences\n Are results-oriented and thrive in fast-paced environments where priorities shift based on research findings\n Care deeply about AI safety and want your work to directly influence how capable AI systems are developed and deployed\n \n Strong candidates may also have:  \n \n Experience building evaluations for long-horizon or agentic tasks\n Deep familiarity with Reinforcement Learning training dynamics and how model behavior changes during training\n Published research in machine learning evaluation, benchmarking, or related areas\n Experience with safety evaluation frameworks and red teaming methodologies\n Background in psychometrics, experimental psychology, or other measurement-focused disciplines\n A track record of communicating evaluation results to inform high-stakes decisions about model development or deployment\n Experience managing or mentoring researchers and engineers\n \n Representative projects:  \n \n Designing and implementing a suite of long-horizon evaluations that test model capabilities on tasks requiring sustained reasoning, planning, and tool use over extended interactions\n Building systems to track capability development across RL training checkpoints, surfacing insights about when and how specific capabilities emerge\n Conducting a cross-org audit of evaluation coverage, identifying blind spots, and prioritizing new evaluations to fill critical gaps across Pretraining, RL, Inference, and Product\n Developing the evaluation methodology and narrative for a major model release, working with research leads and communications to clearly characterize model capabilities and limitations\n Researching and prototyping novel evaluation approaches for capabilities that are difficult to measure with existing benchmarks\n Leading a team","salary_min":850000,"salary_max":850000,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["reinforcement-learning","pre-training","agents","alignment","search","llm","research"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5139654008","is_featured":true,"is_sticky":false,"status":"active","published_at":"2026-03-06T17:15:29Z","expires_at":"2026-06-29T14:00:22.960238Z","created_at":"2026-04-13T09:36:01.625992Z","updated_at":"2026-05-30T14:00:23.075652Z","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/f8c6c621-b459-40f6-b41d-0baa191734ff"},{"id":"3e448289-7fed-4d06-9da9-bd0879a8241b","company_id":"a0000000-0000-0000-0000-000000000003","title":"Manager, Machine Learning Research Scientist, GenAI","slug":"manager-machine-learning-research-scientist-genai-c7602476","description":"Scale AI accelerates the development of AI systems by providing the data, infrastructure, and tooling that power the most advanced models in the world. Our teams operate at the intersection of cutting-edge research, large-scale engineering, and real-world deployment, partnering with leading frontier labs, enterprises, and government agencies to push Generative AI into new capabilities and applications.\n As AI rapidly evolves from static models to dynamic, agentic systems, Scale is building the foundational research, evaluation methodologies, and agent/RL infrastructure that will define this next era. You’ll join a high-impact research organization driving advances in large-language models, post-training, evaluation, and agentic/RL environments, helping shape how next-generation AI is built, measured, and deployed.\n As a Research Scientist Manager, you will lead a world-class team of research scientists and engineers, define the research roadmap, and drive execution from early prototyping to deployment. You’ll thrive in a fast-moving environment, balancing deep technical leadership with people management, vision setting, and delivery.\n You will: \n \n Lead, mentor and grow a team of research scientists and engineers working on GenAI research initiatives (e.g., evaluation, post-training, agents, RL environments).  \n Define and drive a multi-year research roadmap: identify key scientific questions, set milestones, allocate resources, and ensure rigorous execution.\n Collaborate cross-functionally with engineering, product, client-facing teams and external academic or industry partners to translate research into components, insights, and actionable outcomes.\n Communicate compellingly: publish research, present at conferences, engage in open-source contributions, and represent the team externally.\n Drive an inclusive, high-performing culture: help your team through technical challenges, provide growth opportunities, and attract top talent.\n Stay deeply connected to the research community, understanding major trends, and helping set them.\n Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.\n \n Ideally you'd have: \n \n 5+ years of hands-on research experience (PhD or equivalent preferred) in machine learning, deep learning, generative models, agent/rl systems or related domains.\n A strong track record of research excellence, including publications in top-tier ML/AI venues (NeurIPS, ICML, ICLR, ACL, etc.).\n Experience and track of recording in landing major research impacts in a fast-paced environment\n Experience leading or managing research teams. You’re excited to mentor, coach and develop talent.\n Excellent written and verbal communication skills. You are able to articulate research ideas and outcomes to both technical and non-technical stakeholders.\n \n \n Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. \n Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:\n $398,400 — $498,000 USD \n PLEASE NOTE:  Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. \n About Us: \n At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst \u0026 Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. \n We believe that everyone ","salary_min":398400,"salary_max":498000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["agents","generative-ai","deep-learning","machine-learning","research"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4631811005","is_featured":true,"is_sticky":false,"status":"active","published_at":"2025-11-19T00:07:25Z","expires_at":"2026-06-29T14:01:10.349946Z","created_at":"2026-04-13T09:36:44.631119Z","updated_at":"2026-05-30T14:01:10.459208Z","company_name":"Scale AI","company_slug":"scale-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=scale.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3e448289-7fed-4d06-9da9-bd0879a8241b"},{"id":"faa17528-2b03-4b12-9ce4-d471daa30ee2","company_id":"a0000000-0000-0000-0000-000000000001","title":"Engineering Manager, Cybersecurity Products","slug":"engineering-manager-cybersecurity-products-977bce2a","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 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 are hiring an Engineering Manager to lead a team of engineers building AI-powered cybersecurity products. The work spans research, product, and go-to-market.\n Your team will prototype and ship products that use frontier models to defend code and infrastructure. You will set technical direction, partner with research to turn new model capabilities into products, and stay close to customers so the team builds the right things, not just builds things well.\n This is a builder's role. The team is small, the pace is high, and you should expect to be in the code, in customer calls, and in research reviews the same week. You also need to scale the team without losing the prototyping energy that got the product here.\n Responsibilities \n \n \n Lead and grow the team: hiring, performance, and the culture that keeps strong engineers doing their best work\n \n Set technical direction and sequence the roadmap across prototyping, enterprise hardening, and platform investments, with PM and PMM\n \n Partner with research to identify model capabilities worth productizing, and give research clear signal on the capability gaps blocking customer value\n \n Stay close to customers, design partners, and the security community; turn what you learn into product bets and unblock the team on the ones that matter\n \n Make architectural calls across agentic scanning pipelines, model orchestration, customer-facing surfaces, CI and source-control integrations, and the data infrastructure underneath\n \n Raise velocity by removing bottlenecks and sharpening operating rhythms, while holding the bar on quality, security, and reliability\n \n Coordinate with GTM, partnerships, and other product areas to land joint launches and ecosystem integrations\n \n Grow the next layer of leadership on the team so it can take on more as the charter expands\n \n You may be a good fit if you \n \n \n Have 8+ years of software engineering experience and 4+ years managing engineers, with ownership of a team's hiring, performance, and technical direction\n \n Have shipped cybersecurity products in production (SIEM, EDR, vulnerability management, application security, threat detection, incident response, or security automation)\n \n Have taken a team from prototype through first paying customers to scaled enterprise deployment\n \n Are technical and hands-on: comfortable in design reviews and in the team's code\n \n Have strong product instincts and a record of helping teams decide what to build, not just how\n \n Communicate clearly across functions and keep research, product, GTM, and executive partners aligned through ambiguity\n \n Treat direct customer contact as a primary input to your roadmap\n \n Care deeply about Anthropic's mission and about developing AI responsibly and safely\n \n Strong candidates may also have experience with \n \n \n Hands-on security expertise: application security, vulnerability research, reverse engineering, incident response, penetration testing, or detection engineering\n \n Building products on LLMs, including agentic systems, evals, and prompt and model iteration loops\n \n Strict data-handling environments (BYOC, CMEK, regulated industries, governments)\n \n Both startup and enterprise-scale company experience\n \n Working closely with research to translate capability into shipped product\n \n Ecosystem partnerships and MCP, CI/CD, or source-control integrations\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $405,000 — $485,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't a","salary_min":405000,"salary_max":485000,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["llm","security","alignment","agents"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5236531008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-30T03:37:09Z","expires_at":"2026-06-29T14:00:14.304228Z","created_at":"2026-05-30T14:00:14.410288Z","updated_at":"2026-05-30T14:00:14.410288Z","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/faa17528-2b03-4b12-9ce4-d471daa30ee2"},{"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":"577d4902-fac2-40fd-9d40-2f5c20df045a","company_id":"776e5e7d-beba-4889-a481-6d9d7c3af325","title":"Senior Software Engineer, Developer Platform","slug":"senior-software-engineer-developer-platform-f5dcd14a","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\n\nABOUT THE TEAM\n\nThe Infrastructure team builds and operates the foundations that power Decagon: networking, data, ML serving, developer platform, and real‑time voice. We partner closely with product, data, and ML to deliver high‑scale, low‑latency systems with clear SLOs and great developer ergonomics.\n\n\n\n\nABOUT THE ROLE\n\nWe’re looking for a Senior Software Engineer to help build and evolve our internal developer platform—everything from CI/CD and release automation to observability standards, platform tooling, and developer workflows that remove friction.\n\nThis role is for someone who loves making other engineers faster: reducing build times, eliminating flaky tests, creating paved roads for service creation/deployment, and raising the bar on operability by default. Roles like this often combine “builder” energy with strong empathy for how engineers actually work.\n\n\n\n\nWHAT YOU'LL DO\n\n - Developer productivity \u0026 platform tooling\n   \n   - Identify workflow bottlenecks (build/test/release/local dev) and build tools that measurably reduce toil.\n   \n   - Create and maintain “golden paths” like service templates, CLIs, libraries, and automation that teams rely on.\n\n - CI/CD \u0026 release engineering\n   \n   - Design reusable CI pipelines and deployment workflows that are fast, safe, and easy to adopt across teams.\n   \n   - Improve reliability of builds and tests (flake reduction, hermeticity, caching) and drive down cycle time.\n   \n   - Support progressive delivery patterns (canary / blue-green) and safe rollback mechanisms.\n\n - Observability \u0026 operational excellence\n   \n   - Establish shared observability primitives (metrics/logs/traces), standards, and libraries so services are production-ready by default.\n   \n   - Partner with product engineers to improve operability: SLOs, alerting hygiene, dashboards, incident learnings.\n\n - Infrastructure foundations\n   \n   - Build and improve core platform capabilities that make it easy to run and scale services.\n\n - Ownership \u0026 reliability\n   \n   - Own the systems you build end-to-end and help keep them healthy in production, improving reliability over time.\n\n\n\n\nYOUR BACKGROUND LOOKS SOMETHING LIKE THIS\n\n - 4+ years building production software, with meaningful experience in platform / devtools / infrastructure (or adjacent SRE/release engineering).\n\n - Strong coding ability in at least one systems/productivity language (e.g., Python, TypeScript/JS), and comfort building developer-facing tooling (CLIs, libraries, automation).\n\n - Hands-on experience with CI/CD systems and designing pipelines that are scalable and reusable across many repos/services.\n\n - Practical experience with observability in production systems (instrumentation, alerting, dashboards, incident response).\n\n - Comfort with containers and modern cloud infrastructure (e.g., Docker/Kubernetes and related tooling).\n\n - A track record of improving developer experience through measurable outcomes (faster builds, fewer flakes, safer deploys, fewer incidents).\n\n - Strong cross-team collaboration and communication—especially writing clear docs and driving adoption.\n\n\n\n\nEVEN BETTER IF YOU HAVE\n\n - Experience with monorepos and build systems and/or large-scale CI performance work.\n\n - Experience building internal platforms: service templates, paved-road deployment, self-serve environments, developer portals.\n\n - Infrastructure-as-code experience (e.g., Terraform) and a security-minded approach to supply chain (provenance, secrets, least privilege).\n\n - Experience applying AI-assisted tooling to make engineers dramatically more effective.\n\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 ","salary_min":200000,"salary_max":400000,"location":"New York, NY","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["cloud","agents","infrastructure","platform"],"apply_url":"https://jobs.ashbyhq.com/decagon/c15c3dc8-6df7-43ca-aeeb-dc2beed2668e/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T23:19:24.295Z","expires_at":"2026-06-29T14:07:12.463759Z","created_at":"2026-05-30T14:07:12.575972Z","updated_at":"2026-05-30T14:07:12.575972Z","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/577d4902-fac2-40fd-9d40-2f5c20df045a"},{"id":"aae8b669-3776-4de3-8b0f-32302056ea43","company_id":"776e5e7d-beba-4889-a481-6d9d7c3af325","title":"Senior Software Engineer, Data Infrastructure","slug":"senior-software-engineer-data-infrastructure-4c459d4c","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\n\nABOUT THE TEAM\n\nThe Infrastructure team builds and operates the foundations that power Decagon: networking, data, ML serving, developer platform, and real‑time voice. We partner closely with product, data, and ML to deliver high‑scale, low‑latency systems with clear SLOs and great developer ergonomics.\n\nWe organize around four focus areas:\n\n - Core Infra: The foundational cloud stack—networking, compute, storage, security, and infrastructure‑as‑code—to ensure reliability, scale, and cost efficiency.\n\n - Data Infra: Streaming/batch data platforms powering analytics/BI and customer‑facing telemetry, including for customer‑managed and on‑prem environments.\n\n - ML Infra: GPU and model‑serving platforms for LLM inference with multi‑provider routing and support for on‑prem/air‑gapped deployments.\n\n - Platform (DevEx): CI/CD, paved paths, and core services that make shipping fast, safe, and consistent across teams.\n\nOur mission is to deliver magical support experiences — AI agents working alongside humans to resolve issues quickly and accurately.\n\n \n\nAbout the Role\nWe're hiring a Senior Data Infrastructure Engineer to design, build, and operate the data systems that power Decagon's AI products. You'll own critical data pipelines and storage layers end‑to‑end, improve reliability and performance, and create paved paths that let every Decagon engineer work confidently with data at scale.\n\nIn this role, you will\n\n - Design and implement high‑throughput data pipelines and streaming systems with strong SLOs, clear runbooks, and actionable telemetry.\n\n - Build and operate real‑time and batch ingestion infrastructure using tools like Kafka, Flink, and Airflow.\n\n - Own our analytical data layer — schema design, query performance, and cost optimization across ClickHouse, BigQuery, or similar.\n\n - Partner with research and product teams to architect data solutions, evaluate performance, and scale new features.\n\n - Tune pipeline and query latencies: optimize data paths, apply smart caching/partitioning, and hit tight p95/p99 targets.\n\n - Lead infrastructure‑as‑code (Terraform) and GitOps practices for data systems; reduce drift with reusable modules and policy‑as‑code.\n\n - Participate in on‑call and drive down toil through automation and elimination of recurring data issues.\n\nYour background looks something like this\n\n - 5+ years building and operating production data infrastructure at scale.\n\n - Hands-on experience with Tier 1 data technologies: ClickHouse, Kafka (or MSK/Pub‑Sub/RabbitMQ), and Flink or dbt.\n\n - Proven track record meeting high availability and low latency targets across streaming and batch workloads.\n\n - Excellent observability chops (OpenTelemetry, Prometheus/Grafana, Datadog) and strong incident response discipline.\n\n - Clear written communication and the ability to turn ambiguous data requirements into simple, reliable designs.\n\nEven better if you have\n\n - Experience with CDC tooling (Debezium) and orchestration frameworks (Airflow, Dagster, or Prefect)\n\n - Familiarity with Spark or Dask for large‑scale data processing\n\n - Experience with cloud data warehouses (Snowflake, BigQuery, Redshift, Databricks)\n\n - Experience being an early data/platform/infrastructure engineer at another company\n\n - Strong Kubernetes experience (GKE/EKS/AKS) and multi‑cloud exposure (GCP, AWS, Azure)\n\n - Experience with customer‑managed deployments\n\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 (","salary_min":200000,"salary_max":400000,"location":"New York, NY","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["agents","llm","data-pipeline","infrastructure"],"apply_url":"https://jobs.ashbyhq.com/decagon/0d0beb6b-61a2-40e3-9955-adcff9cbc92e/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T23:17:54.192Z","expires_at":"2026-06-29T14:07:13.674618Z","created_at":"2026-05-30T14:07:13.790812Z","updated_at":"2026-05-30T14:07:13.790812Z","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/aae8b669-3776-4de3-8b0f-32302056ea43"},{"id":"3b0f1d10-c226-4905-9392-d5d4cdceab10","company_id":"776e5e7d-beba-4889-a481-6d9d7c3af325","title":"Senior Software Engineer, Data Infrastructure","slug":"senior-software-engineer-data-infrastructure-20b94406","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\n\nABOUT THE TEAM\n\nThe Infrastructure team builds and operates the foundations that power Decagon: networking, data, ML serving, developer platform, and real‑time voice. We partner closely with product, data, and ML to deliver high‑scale, low‑latency systems with clear SLOs and great developer ergonomics.\n\nWe organize around four focus areas:\n\n - Core Infra: The foundational cloud stack—networking, compute, storage, security, and infrastructure‑as‑code—to ensure reliability, scale, and cost efficiency.\n\n - Data Infra: Streaming/batch data platforms powering analytics/BI and customer‑facing telemetry, including for customer‑managed and on‑prem environments.\n\n - ML Infra: GPU and model‑serving platforms for LLM inference with multi‑provider routing and support for on‑prem/air‑gapped deployments.\n\n - Platform (DevEx): CI/CD, paved paths, and core services that make shipping fast, safe, and consistent across teams.\n\nOur mission is to deliver magical support experiences — AI agents working alongside humans to resolve issues quickly and accurately.\n\n\n\nAbout the Role\nWe're hiring a Senior Data Infrastructure Engineer to design, build, and operate the data systems that power Decagon's AI products. You'll own critical data pipelines and storage layers end‑to‑end, improve reliability and performance, and create paved paths that let every Decagon engineer work confidently with data at scale.\n\nIn this role, you will\n\n - Design and implement high‑throughput data pipelines and streaming systems with strong SLOs, clear runbooks, and actionable telemetry.\n\n - Build and operate real‑time and batch ingestion infrastructure using tools like Kafka, Flink, and Airflow.\n\n - Own our analytical data layer — schema design, query performance, and cost optimization across ClickHouse, BigQuery, or similar.\n\n - Partner with research and product teams to architect data solutions, evaluate performance, and scale new features.\n\n - Tune pipeline and query latencies: optimize data paths, apply smart caching/partitioning, and hit tight p95/p99 targets.\n\n - Lead infrastructure‑as‑code (Terraform) and GitOps practices for data systems; reduce drift with reusable modules and policy‑as‑code.\n\n - Participate in on‑call and drive down toil through automation and elimination of recurring data issues.\n\nYour background looks something like this\n\n - 5+ years building and operating production data infrastructure at scale.\n\n - Hands-on experience with Tier 1 data technologies: ClickHouse, Kafka (or MSK/Pub‑Sub/RabbitMQ), and Flink or dbt.\n\n - Proven track record meeting high availability and low latency targets across streaming and batch workloads.\n\n - Excellent observability chops (OpenTelemetry, Prometheus/Grafana, Datadog) and strong incident response discipline.\n\n - Clear written communication and the ability to turn ambiguous data requirements into simple, reliable designs.\n\nEven better if you have\n\n - Experience with CDC tooling (Debezium) and orchestration frameworks (Airflow, Dagster, or Prefect)\n\n - Familiarity with Spark or Dask for large‑scale data processing\n\n - Experience with cloud data warehouses (Snowflake, BigQuery, Redshift, Databricks)\n\n - Experience being an early data/platform/infrastructure engineer at another company\n\n - Strong Kubernetes experience (GKE/EKS/AKS) and multi‑cloud exposure (GCP, AWS, Azure)\n\n - Experience with customer‑managed deployments\n\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 (subj","salary_min":200000,"salary_max":400000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["llm","data-pipeline","agents","infrastructure"],"apply_url":"https://jobs.ashbyhq.com/decagon/d400020b-2f97-4316-a8c2-9dc70f254cdd/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T23:14:29.883Z","expires_at":"2026-06-29T14:07:13.754967Z","created_at":"2026-05-30T14:07:13.876706Z","updated_at":"2026-05-30T14:07:13.876706Z","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/3b0f1d10-c226-4905-9392-d5d4cdceab10"},{"id":"a3d16455-f42f-4915-8723-2d023a5b665b","company_id":"2ca4efa5-edc2-4352-a597-ea27086e1e5b","title":"Senior Software Engineer II, AI Labs \u0026 Foundations","slug":"senior-software-engineer-ii-ai-labs-foundations-e74eb4cd","description":"We're transforming the grocery industry \n At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. \n Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.\n Instacart is a Flex First team \n There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. \n Overview\n Join Instacart's mission to transform grocery shopping through frontier AI. As a Senior Software Engineer on AI Labs \u0026 Foundations, you will design, build, and operate the high-scale production systems that power our most ambitious AI experiences—from Cart Assistant, our conversational shopping agent, to voice AI interactions and beyond. This is a high-impact opportunity to work at the intersection of robust software engineering and cutting-edge production AI/ML, directly shaping products used by millions of customers every day.\n We are hiring a Senior Software Engineer who will participate in the design and delivery of production AI systems, identify high-leverage technical opportunities, and contribute hands-on to AI-native products across Instacart's platform. We value bottom-up ideas, high engineering quality, and close partnership with Product, Data Science, ML, and Infrastructure teams. If you enjoy inventing, navigating ambiguity, prototyping fast, and turning wild ideas into real, scalable products, this is the team for you.\n AI Labs \u0026 Foundations sits at the intersection of frontier AI research and production engineering. Our portfolio spans the full stack of AI innovation at Instacart, including building and launching Cart Assistant, pioneering voice AI interactions, and constructing the foundational systems that power these cutting-edge experiences. We are a fast-moving, collaborative team that thrives on 0-to-1 thinking, shares learnings openly, and ships with urgency by prototyping fast and testing rigorously.\n About the Job\n \n Design, build, and operate production AI-powered systems and agentic experiences (including Cart Assistant and voice AI) that directly impact how millions of customers shop.\n Build foundational systems for cutting-edge AI experiences, ranging from embedding infrastructure and voice AI pipelines, to client facing components and integrations, by prototyping bold ideas and productizing what works.\n Integrate foundation models via APIs and open-source frameworks; apply techniques like retrieval-augmented generation and vector search where appropriate.\n Own projects end-to-end: requirements, technical design, implementation, testing, deployment, observability, and iterative improvement focused on reliability, latency, and cost efficiency.\n Collaborate with cross-functional partners in product, design, data science, and infrastructure to ship AI features end-to-end.\n Drive engineering excellence, including thoughtful system design, rigorous code review, and technical leadership that includes defining and promoting best practices for AI/ML production engineering across the team.\n \n About You\n Minimum Qualifications: \n \n Proven senior software engineer who has built, shipped, and operated production systems at scale. You make architectural calls, own what you build, and deliver through ambiguity.\n Hands-on experience with AI or ML in production. You've shipped LLM-powered features or integrated foundation model APIs into a live product, demonstrating the necessary expertise at the intersection of robust software engineering and deep production ML.\n Experience owning services end-to-end, including CI/CD, automated testing, observability (logging, metrics, tracing), and on-call participation.\n Strong communicator who partners well across disciplines - you want to get to the right answer, not just defend the first one.\n Excitement and ability to leverage cutting-edge development tools, including AI assistance (e.g., Copilot, Cursor, Claude), to maximize velocity.\n \n Preferred Qualifications: \n \n 5 to 8+ years of industry experience.\n A track record of 0-to-1 work taking unconventional ideas from prototype through rapid iteration to production.\n Experience building conversational agents, multi-turn dialogue systems, or agentic LLM applications.\n Exp","salary_min":192000,"salary_max":202000,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["cloud","fine-tuning","code-generation","generative-ai","llm","distributed-systems","agents","speech"],"apply_url":"https://instacart.careers/job/?gh_jid=7951041","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T22:43:14Z","expires_at":"2026-06-29T14:08:42.057285Z","created_at":"2026-05-30T14:08:42.180879Z","updated_at":"2026-05-30T14:08:42.180879Z","company_name":"Instacart","company_slug":"instacart","company_logo_url":"https://www.google.com/s2/favicons?domain=www.instacart.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a3d16455-f42f-4915-8723-2d023a5b665b"},{"id":"14a818b5-1068-4d53-8e01-2106c013d919","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Software Engineer, Operational/ Process Efficiency ","slug":"software-engineer-operational-process-efficiency-0675432b","description":"Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.\n This role is at the intersection of robotics and machine learning, driving the next generation of operational efficiency for Waymo's rapidly expanding autonomous fleet. You will lead efforts to generalize complex depot operations—such as exterior cleaning, sensor calibration, and maintenance checks—using advanced robotics. Key work involves leveraging foundation models, reinforcement learning, simulation, and integrating ML models in production at scale. You will interface closely with operations teams to translate real-world needs into robust, working solutions.\n This role follows a hybrid work schedule and reports to a Director, Hardware and Sensors. \n You will: \n \n Drive the automation of the hardware lifecycle for critical sensors (lidar, radar, cameras) and compute modules.\n Develop and deploy agentic systems and foundation models to streamline workflows between internal teams and contract manufacturers.\n Identify opportunities to apply AI to manufacturing, installation, and troubleshooting processes to increase operational velocity.\n Interface with a diverse set of stakeholders, including hardware design engineers, failure analysis engineers, and diagnostic teams, to translate physical requirements into technical specifications.\n Bridge the gap between experimental ML models and high-scale production environments.\n \n You have: \n \n A Masters or PhD in Machine Learning, Computer Science, or a related technical field.\n A proven track record of delivering working engineering solutions, balancing scientific rigor with production needs.\n Experience in training, evaluating, and deploying machine learning models at scale.\n Strong communication skills and the ability to collaborate across multidisciplinary teams (from field technicians to hardware designers).\n \n We prefer: \n \n Hands-on experience or deep familiarity with agentic tools and frameworks.\n Experience working with large-scale foundation models (LLMs, VLMs) and fine-tuning them for specialized domains.\n Background in automating industrial or hardware-centric workflows.\n Familiarity with hardware diagnostics, failure analysis, or manufacturing processes.\n \n  \n The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.  \n Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.  \n Salary Range\n $175,000 — $215,000 USD","salary_min":175000,"salary_max":215000,"location":"Mountain View, CA","workplace":"hybrid","job_type":"full-time","experience_level":"mid","tags":["agents","generative-ai","robotics","autonomous-vehicles","llm","reinforcement-learning","fine-tuning"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=7926526","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T20:26:39Z","expires_at":"2026-06-29T14:04:30.317025Z","created_at":"2026-05-30T14:04:30.42607Z","updated_at":"2026-05-30T14:04:30.42607Z","company_name":"Waymo","company_slug":"waymo","company_logo_url":"https://www.google.com/s2/favicons?domain=waymo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/14a818b5-1068-4d53-8e01-2106c013d919"},{"id":"73600478-6692-47ce-be77-2aebfb5bb4a2","company_id":"82d2abc2-444c-4d89-9646-4739e72d700d","title":"Machine Learning Engineer","slug":"machine-learning-engineer-5aefaff6","description":"About Checkr Checkr is building the data platform to power safe and fair decisions. Over 140,000 companies and millions of people rely on Checkr for AI verification in the moments that matter most: getting a new job, a new place to live, a car ride, childcare, even a date. Customers include Uber, Pennymac, Airbnb, Doordash, Amazon, and Anthropic. We’re a team that thrives on solving complex problems with innovative solutions that advance our mission. Checkr is recognized on Forbes Cloud 100 2025 List and is a Y Combinator 2024 Breakthrough Company .\n About the team/role \n We’re hiring an ML Engineer (P2) to build and ship the AI systems that power Checkr’s core products. This role sits on the ML team inside Checkr’s Data \u0026 ML organization within Engineering.\n Checkr runs millions of background checks a year. The ML team builds the systems that make those checks faster, more accurate, and cheaper to operate: document processing, charge classification, entity resolution, and in-product intelligence. These are production services that Product Engineering depends on daily.\n This is not a research role or a notebook role. You’ll own ML services end-to-end: design them, code them, deploy them, monitor them. We need someone who writes production software, builds with LLMs and APIs as first-class tools, and can tell the difference between working code and AI slop. If you’ve spent the last few years building AI-native software and you care deeply about engineering craft, we want to talk.\n This role sits in the central Data \u0026 ML team within the Engineering organization. You will partner daily with Product Engineering, Product, and cross-functional teams. You’ll also contribute to Checkr’s broader AI strategy, including our initiative to deploy our agentic fleet and build scalable context with our semantic layer.\n We are looking for someone based in San Francisco who has built ML systems in fast-moving, impact-first environments. Less process, more shipping. Less paperwork, more results.\n  \n What you’ll do \n \n Build and deploy ML/AI services. Design, develop, and ship ML models and AI systems that Product Engineering teams rely on. You write the model code, the API layer, the monitoring, and the tests. Not notebooks; production services.\n Design with LLMs and APIs. Use LLM APIs (OpenAI, Anthropic, etc.) as building blocks in production systems. You know when to call an LLM, when to fine-tune, when to use a classical model, and when to write a rule. You think about cost, latency, and quality together.\n Ship production software. Write clean, well-structured code with solid OOP, proper abstractions, error handling, and tests. Your code gets reviewed by SWEs and passes. CI/CD is how you work, not something you bolt on at the end.\n Partner with product and engineering. Translate business problems into ML solutions. Define API contracts with product engineers. Explain your approach clearly to non-ML partners and leave the room with alignment, not confusion.\n Evaluate and iterate fast. Build evaluation frameworks, run experiments, and make data-driven decisions about model and system performance. Ship and iterate; don’t wait for perfect.\n Ship AI-powered workflows. Put AI to work on your own processes: automate pipelines, build agentic workflows, and contribute reusable skills and context to Checkr’s agentic platform. The expectation is that our teams operate AI-first.\n \n What you bring \n \n A Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field, or equivalent depth from experience\n 4+ years building software professionally, with at least 2 of those building ML systems that run in production\n Strong Python fluency; you write clean, testable, well-structured code with solid OOP instincts. Not scripts; software\n Hands-on experience using LLM APIs in production systems: prompt engineering, structured outputs, function calling, cost management, and evaluation\n You’ve built and maintained APIs, worked with CI/CD pipelines, and shipped code that other engineers depend on\n Comfortable with distributed systems concepts: queues, async processing, caching, horizontal scaling\n Experience with NLP tasks in production: classification, extraction, entity resolution, summarization\n Comfort with and enthusiasm for AI-assisted workflows; experience using LLMs, code-generation tools, or agentic systems in production or operational contexts is a strong signal\n You can evaluate tradeoffs: fine-tune vs. prompt, hosted vs. self-deployed, classical ML vs. LLM, rule vs. model\n Strong communication skills; you explain technical decisions clearly to engineers and non-engineers alike, without hiding behind jargon\n You use AI tools (Copilot, Claude, etc.) to move faster, but you understand every line they produce. You can spot AI slop and you don’t ship it\n An A-player mindset with a strong bias for action: you raise the bar, move with urgency, stay resilient through ambiguity, and t","salary_min":168000,"salary_max":198000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"mid","tags":["nlp","code-generation","mlops","agents","payments","legal","distributed-systems","llm"],"apply_url":"https://job-boards.greenhouse.io/checkr/jobs/7966920","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T15:17:56Z","expires_at":"2026-06-29T14:10:31.076983Z","created_at":"2026-05-30T14:10:31.19215Z","updated_at":"2026-05-30T14:10:31.19215Z","company_name":"Checkr","company_slug":"checkr","company_logo_url":"https://www.google.com/s2/favicons?domain=checkr.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/73600478-6692-47ce-be77-2aebfb5bb4a2"},{"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":"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":"999579f7-1c88-4dd4-b7e2-d60e2aada335","company_id":"e12d7a84-7538-4599-9b03-0cce91dc76b4","title":"AI Engineer","slug":"ai-engineer-b1ab9615","description":"GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster.\n The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software.\n * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. \n An overview of this role \n As an AI Engineer at GitLab, you'll help build the foundation for GitLab's transformation into an AI-first company. Reporting to the Director, Enterprise AI, you'll be a hands-on technical leader responsible for delivering internal AI-powered solutions that drive measurable business outcomes.\n Building fast matters, but it's not enough on its own. This role starts with understanding the real problem: mapping how work moves across teams, tools, and handoffs, identifying the true constraint, and validating whether AI is the right solution before you begin development. From there, you'll take ownership from discovery through deployment, combining strong engineering skills with systems thinking and business understanding.\n Your initial focus will span Sales, Marketing, and Customer Support, where you will embed AI solutions into key systems and workflows. This role offers the opportunity to shape how GitLab team members work, improve flow across the organization, and help advance our mission in a remote, asynchronous, and values-driven environment.\n What you'll do \n \n Diagnose business problems before building solutions. Map workflows, identify constraints, and confirm whether AI is the right intervention. Be prepared to say \"this doesn't need AI\" when that's the honest answer.\n Own AI initiatives end-to-end, from stakeholder discovery and technical design through implementation, deployment, and iteration.\n Design, develop, and ship AI-powered solutions quickly, delivering working prototypes in days, not months, with a focus on practical outcomes and measurable business value.\n Improve organizational flow by building solutions that reduce bottlenecks, shorten lead times, and increase throughput. Measure success using flow metrics alongside adoption and ROI.\n Integrate AI capabilities into existing systems and workflows using APIs, orchestration tools, and modern AI platforms, including GitLab Duo Agent Platform, where appropriate. The right tool wins, whether that's custom code, a platform, or a well-crafted prompt.\n Be Customer Zero: leverage and showcase GitLab's AI offerings wherever possible, feeding real-world usage insights back to R\u0026D.\n Partner closely with stakeholders across functions to understand the real constraints. Ask the right questions, bridge technical and non-technical perspectives, and align on outcomes before jumping to solutions.\n Define and track success through business metrics, flow metrics, and feedback loops that make performance visible and actionable.\n Contribute to technical direction by evaluating tools, documenting patterns, and creating reusable foundations that help the team scale its impact.\n \n What you'll bring \n \n A Technologist at Heart -  Genuinely invested in technology, the foundational and the cutting-edge in equal measure. You're as energised by a well-designed API integration as you are by the latest foundation model release. You reach for the simplest solution that solves the problem well, rather than forcing new technology when proven approaches would do. AI is a powerful part of your toolkit, but it sits on top of solid engineering fundamentals, not in place of them.\n Competent, Confident Coding Skills -  You can build working solutions end-to-end, write clean and maintainable code, and debug effectively. Whether your skills were honed in a traditional engineering role, through building automations, or shipping side projects, what matters is that you can deliver production-quality work independently.\n AI  \u0026 LLM  Technical Depth -  Strong proficiency in at least one modern scripting language (Pyth","salary_min":108400,"salary_max":129600,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"mid","tags":["alignment","llm","api-design","generative-ai","rag","agents"],"apply_url":"https://job-boards.greenhouse.io/gitlab/jobs/8565469002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T11:49:29Z","expires_at":"2026-06-29T14:08:37.633939Z","created_at":"2026-05-29T14:32:31.013898Z","updated_at":"2026-05-30T14:08:37.751307Z","company_name":"GitLab","company_slug":"gitlab","company_logo_url":"https://www.google.com/s2/favicons?domain=about.gitlab.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/999579f7-1c88-4dd4-b7e2-d60e2aada335"},{"id":"960ff8ca-6a38-4ffc-893e-dd306a5479c9","company_id":"1c5cd464-c475-4739-a226-7268fa45343a","title":"Digital Customer Programs Manager","slug":"digital-customer-programs-manager-06d80811","description":"ABOUT ASSEMBLED\n\nGreat customer support requires human agents and AI in perfect balance, and Assembled https://www.assembled.com/customers is the only unified platform that orchestrates both at scale. Companies like Canva, Etsy, and Robinhood use Assembled to coordinate their entire support operation — in-house agents, BPOs, and AI — in a single operating system. With AI Agents that resolve cases end-to-end, AI Copilot for agent assistance, and AI-powered workforce management that optimizes both human and AI capacity, Assembled helps teams deliver faster, better service while making smarter decisions about how to staff and automate. Backed by $71M from NEA, Emergence Capital, and Stripe, we're building the platform that makes AI and human collaboration actually work.\n\n\n\n\nTHE ROLE\n\nThe Digital Customer Programs Manager owns Assembled's Scale tier customer experience. The Scale tier is served through structured programs: self-serve resources, community engagement, and light-touch human interaction — not an assigned CSM relationship. This role sits in the Support org, within our broader Customer Experience department, and that's intentional. When customers hit technical friction, the response needs to be as disciplined as it is empathetic. You'll move fluidly between customer success instincts and technical support process rigor, with impact measured across the entire tier, not a single account list.\n\n\n\nYou'll be the primary executor of the Scale Experience program — high daily volume, a wide range of customer maturity levels, and constant context-switching. If you're energized by breadth and by building things that scale, this is your role.\n\n\n\n\nRESPONSIBILITIES\n\n - Account Health Monitoring — Own or help build the systematic mechanism for tracking health signals across the tier. Know which accounts are engaged, which are drifting, and why. Engage when signals change — don't wait for a renewal to address misalignments.\n\n - Renewals — Proactively manage the renewal motion for this tier, using health data to get ahead of risk well before renewal dates. Facilitate pre-renewal check-ins for accounts showing growth potential or as needed to address questions on terms, value, legal or contract details.\n\n - Office Hours — Staff scheduled 1:1 sessions for Scale customers alongside the support team, tag-teaming with support engineers based on the account and nature of the request. Sessions cover product questions, troubleshooting, and relationship or commercial topics. Log contact drivers to inform knowledge base priorities and product feedback.\n\n - Community \u0026 Engagement — Own Assembled's customer community presence across channels and formats. This may include digital community platforms, webinars, events, forums, the Assembled Slack community, or other programming. Moderate discussions, respond to questions, surface relevant resources, and identify accounts with high potential or in need of additional support.\n\n - Customer Feedback \u0026 Surveys — Own the survey cadence for the Scale tier: design, send, monitor response rates, synthesize results, and surface themes to leadership. Partner with cross-functional owners of survey tooling to coordinate timing and ensure results are actioned across the customer experience.\n\n - Tier Upgrade Flagging — When a Scale customer's needs or growth trajectory warrant a commercial conversation, you own identifying it and routing it appropriately. You're protecting the model, not just the relationship.\n\n - Support Integration — Work hand-in-hand with support engineering across all customer touch points. File tickets, triage issues, own communication on escalations, and respect established support workflows. You're not a support engineer, but you operate like someone who understands why process discipline makes the whole system work.\n\nYou'll know you're succeeding when Scale tier churn is low, renewal rates are healthy, and CSAT and NPS for this segment are at or above industry benchmarks.\n\n\n\n\nABOUT YOU\n\n - You know what it feels like to be on the other side of a scale tier experience. You've been in the weeds of customer-facing work and you bring that empathy into every interaction. You understand the world of support professionals and what good actually looks like to them.\n\n - You've been in a high-volume customer-facing role. You've managed more accounts than you could possibly give individual attention to, and you figured out how to make that work. You understand the difference between a customer who needs more of your time and a customer who needs better resources.\n\n - You hold the line without losing the relationship. When a customer asks for a dedicated CSM, a custom QBR, or a direct line to engineering, you know how to reset expectations in a way that leaves them feeling heard rather than rejected. You've had hard renewal conversations and didn't spiral.\n\n - You respect the power of process. You file the ticket and set expectations (internally \u0026 externally","salary_min":120000,"salary_max":150000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"junior","tags":["agents","llm","code-generation","payments"],"apply_url":"https://jobs.ashbyhq.com/assembledhq/66164c16-1b36-498d-a9d5-7e34ad543d2f/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T05:50:42.725Z","expires_at":"2026-06-29T14:12:01.005639Z","created_at":"2026-05-29T14:47:55.874652Z","updated_at":"2026-05-30T14:12:01.117957Z","company_name":"Assembled","company_slug":"assembled","company_logo_url":"https://www.google.com/s2/favicons?domain=assembled.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/960ff8ca-6a38-4ffc-893e-dd306a5479c9"},{"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":"06abea54-0601-42e3-bb89-32ddb1ee619d","company_id":"3029e985-56bf-4ac2-9ae1-df4cdd53b12f","title":"Sr. Staff Software Development Engineer-AI Security","slug":"sr-staff-software-development-engineer-ai-security-6fd417d1","description":"About Zscaler \n Zscaler accelerates digital transformation to ensure our customers can be more agile, efficient, resilient, and secure. As an AI-forward enterprise , we are constantly pushing the envelope, leveraging the world’s largest security data lake to power our cloud-native Zero Trust Exchange platform. This innovation protects our customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location.\n Here, impact in your role matters more than title and trust is built on results. We say, impact over activity. We seek innovators who actively use AI to amplify their impact and who thrive in an environment where we leverage intelligent systems to stay ahead of evolving threats. We believe in transparency and value constructive, honest debate —we’re focused on getting to the best ideas, faster. We build high-performing teams that can make an impact quickly and with high quality. To do this, we are building a culture of execution centered on customer obsession , collaboration, ownership, and accountability.\n We value high-impact, high-accountability with a sense of urgency where you’re enabled to do your best work and embrace your potential. If you’re driven by purpose, thrive on solving complex challenges, and want to be part of the team that’s helping to secure the AI age, we invite you to bring your talents to Zscaler and help shape the future of cybersecurity.\n Role \n We are looking for a Sr. Staff Software Development Engineer-AI Security to join us as a founding member of our AI Security Team. This is a Hybrid role based in San Jose, CA or Bellevue, WA (3 days in office), reporting to the Director of Software Engineering within the Emerging Tech org.\n You will be responsible for designing and implementing core infrastructure components and distributed systems, serving as a foundational architect for our AI security solution. This high-impact role focuses on scaling security infrastructure to support hundreds of millions of users, collaborating with stakeholders across the development lifecycle to drive innovation and technical excellence.\n What you’ll do (Role Expectations) \n \n Architect, develop, and optimize a low-latency, high-throughput AI Security plane utilizing Rust, specifically leveraging its async/await model for highly efficient I/O and service-oriented architecture\n Build resilient, distributed, and scalable systems, emphasizing concurrency, fault tolerance, and robust messaging protocols\n Implement and maintain gRPC services and APIs to ensure seamless integration of the AI Security plane with control and orchestration infrastructure\n Systematically enhance performance across the entire stack, including LLM models, by employing profiling tools for both kernel-space and user-space components\n Lead complex, multi-functional projects and initiatives, defining the technical roadmap and driving execution across teams\n \n Who You Are (Success Profile) \n \n You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.\n You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution.\n You are a problem-solver. You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact.\n You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.\n You are a learner. You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose.\n \n What We’re Looking for (Minimum Qualifications) \n \n 8+ years of software engineering experience\n Deep experience in systems programming using Rust, with a focus on asynchronous frameworks such as Tokio or async-std\n Proven ability to design and implement horizontally scalable, highly available, and observable distributed systems\n Strong command of Linux internals, including kernel-user space interaction, networking, sockets, and namespaces\n Skilled in performance instrumentation, containerized environments, Git workflows, and CI/CD pipelines\n \n What Will Make You Stand Out (Preferred Qualifications) \n \n Expert in systems languages such as C/C++ or Rust, with a focus on performance optimization\n Deep understanding of Linux networking stacks, Kubernetes networking, service meshes, and LLM model optimization\n ","salary_min":154000,"salary_max":220000,"location":"Bellevue, WA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["security","distributed-systems","api-design","llm","data-pipeline","agents"],"apply_url":"https://job-boards.greenhouse.io/zscaler/jobs/5146138007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T15:07:34Z","expires_at":"2026-06-29T14:09:19.468531Z","created_at":"2026-05-29T14:33:11.60717Z","updated_at":"2026-05-30T14:09:19.582996Z","company_name":"Zscaler","company_slug":"zscaler","company_logo_url":"https://www.google.com/s2/favicons?domain=zscaler.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/06abea54-0601-42e3-bb89-32ddb1ee619d"}],"page":1,"per_page":20,"total":2589,"total_pages":130}