{"has_next":true,"jobs":[{"id":"48720738-0f4b-483d-9739-14039ae457d0","company_id":"a0000000-0000-0000-0000-000000000001","title":"Research Engineer, Performance RL","slug":"research-engineer-performance-rl-2f0da25a","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 RL Teams \n Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Sonnet 4.6 and Opus 4.6. Our work spans several key areas:\n \n \n Developing systems that enable models to use computers effectively\n \n Advancing code generation through reinforcement learning\n \n Pioneering fundamental RL research for large language models\n \n Building scalable RL infrastructure and training methodologies\n \n Enhancing model reasoning capabilities\n \n We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish.\n About the Role \n We're hiring for the Code RL team within the RL organization. As a Research Engineer, you'll advance our models' ability to safely write correct, fast code for accelerators.\n You'll need to know accelerator performance well to turn it into tasks and signals models can learn from. Specifically, you will:\n \n \n Invent, design and implement RL environments and evaluations.\n \n Conduct experiments and shape our research roadmap.\n \n Deliver your work into training runs.\n \n Collaborate with other researchers, engineers, and performance engineering specialists across and outside Anthropic.\n \n You may be a good fit if you:\n \n \n Have expertise with accelerators (CUDA, ROCm, Triton, Pallas), ML framework programming (JAX or PyTorch).\n \n Have worked across the stack – kernels, model code, distributed systems.\n \n Know how to balance research exploration with engineering implementation.\n \n Are passionate about AI's potential and committed to developing safe and beneficial systems.\n \n Strong candidates may also have:\n \n \n Experience with reinforcement learning.\n \n Experience porting ML workloads between different types of accelerators.\n \n Familiarity with LLM training methodologies.\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 $350,000 — $850,000 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 able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a ","salary_min":350000,"salary_max":850000,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"principal","tags":["reinforcement-learning","gpu","code-generation","distributed-systems","search","jax","fine-tuning","llm"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5160330008","is_featured":true,"is_sticky":true,"status":"active","published_at":"2026-03-23T16:27:59Z","expires_at":"2026-06-29T14:00:21.52187Z","created_at":"2026-04-13T09:36:00.086246Z","updated_at":"2026-05-30T14:00:21.633054Z","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/48720738-0f4b-483d-9739-14039ae457d0"},{"id":"60c7aa2a-21b2-4ed4-997e-01e06f7425d0","company_id":"a0000000-0000-0000-0000-000000000003","title":"Director, Enterprise Machine Learning \u0026 Research","slug":"director-enterprise-machine-learning-research-1923b033","description":"The Enterprise ML team works on the front lines of the AI revolution, partnering deeply with customers to identify high-impact business problems and build cutting-edge AI systems using Scale’s proprietary research, data, and infrastructure—unlocking domain expertise through high-quality data and expert feedback.\n As Director of Enterprise ML, 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 This role is ideal for a leader who thrives in ambiguity, understands both frontier GenAI capabilities and their limitations, and is motivated by turning research into durable, production-ready systems.\n What You’ll Do \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 What We’re Looking For \n Core Qualifications \n \n 8+ 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 Exceptional communication and stakeholder management skills, with the ability to influence executives, customers, and cross-functional partners\n \n Nice to Have \n \n Hands-on experience building and deploying agent-based, tool-augmented, or workflow-driven LLM systems in enterprise environments\n Prior ownership of enterprise AI platforms, internal ML products, or customer-facing AI services at scale\n Proven track record of partnering directly with enterprises to identify high-impact use cases and deliver measurable business outcomes\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 $289,800 — $362,250 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","salary_min":289800,"salary_max":362250,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["deep-learning","llm","generative-ai","machine-learning","research"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4679727005","is_featured":true,"is_sticky":false,"status":"active","published_at":"2026-03-31T18:05:38Z","expires_at":"2026-06-29T14:01:07.494675Z","created_at":"2026-04-13T09:36:42.207592Z","updated_at":"2026-05-30T14:01:07.606238Z","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/60c7aa2a-21b2-4ed4-997e-01e06f7425d0"},{"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":"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":"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":"09d0acb5-52de-4a76-88c6-0eb844785025","company_id":"053355fc-0162-4bb9-b414-cbf7679ee9c8","title":"Research Scientist - RL Training","slug":"research-scientist-rl-training-ffdbae39","description":"About Snorkel \n At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.\n We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!\n ABOUT THE ROLE  \n We're looking for a Research Scientist to work on reinforcement learning for training and aligning large language models. This is a foundational research role focused on one of the most consequential open data problems in AI: how to generate the data, reward signals, and training procedures that steer LLM behavior in reliable and generalizable directions — and a core capability that directly differentiates Snorkel's data-as-a-service offering. \n You'll work closely with Snorkel's research, engineering, and delivery teams to advance our RL data capabilities — translating research ideas into the preference datasets, reward models, and RL-ready corpora we produce for frontier AI labs, and contributing to a research agenda that is central to Snorkel's long-term differentiation as a provider of bespoke training data. \n MAIN RESPONSIBILITIES  \n \n Research and implement reinforcement learning techniques — including GRPO, RLHF, RLAIF, DPO, and reward modeling — and translate them into data products (preference datasets, reward signals, verifiable rewards) that customers can use to train and fine-tune large language models. \n Design and build data pipelines that generate high-quality training signal for RL workflows, including AI-assisted data annotation and curation data pipelines to improve model generalization to unseen benchmarks . \n Prototype and iterate on end-to-end RL training recipes that inform what data Snorkel ships as part of its data-as-a-service deliveries. \n Work closely with research scientists, ML engineers, and delivery teams to translate RL research into customer-ready data products.\n Stay current with the latest developments in large-scale muli-node LLM training, alignment research, and scalable RL methods (on complex environments such as Terminal-Bench), bringing relevant advances into Snorkel's data-as-a-service approach.\n Contribute to Snorkel's research publications and internal knowledge base in RL and model training.\n \n PREFERRED QUALIFICATIONS  \n \n Deep expertise in reinforcement learning from human or AI feedback, reward modeling and credit attribution ideally with a clear perspective on what data makes these techniques work. \n Experience training or fine-tuning 30B+ large language models at scale, including familiarity with distributed training infrastructure. \n Strong proficiency in Python and ML frameworks, especially PyTorch and HuggingFace and hands-on experience with RL frameworks such as Verl and SkyRL. \n Solid software engineering fundamentals — you can build research prototypes that others can run, extend, and integrate into data production workflows. \n Familiarity with ML infrastructure and cloud platforms and tools (AWS, GCP, Kubernetes, Slurm, etc.); experience with large-scale RL training pipelines a strong plus. \n Comfort operating in a high-iteration environment with open-ended research questions and shifting, customer-driven technical constraints. \n Ph.D. in machine learning, reinforcement learning, or a related field strongly preferred; exceptional industry experience considered. \n Salary Range \n $200,000 — $325,000 USD \n Be Your Best at Snorkel \n Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.\n Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and haras","salary_min":200000,"salary_max":325000,"location":"Redwood City, CA","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["alignment","distributed-systems","pytorch","fine-tuning","generative-ai","data-pipeline","llm","reinforcement-learning"],"apply_url":"https://job-boards.greenhouse.io/snorkelai/jobs/6009496004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T21:22:40Z","expires_at":"2026-06-29T14:03:05.747327Z","created_at":"2026-05-30T14:03:05.857458Z","updated_at":"2026-05-30T14:03:05.857458Z","company_name":"Snorkel AI","company_slug":"snorkel-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=snorkel.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/09d0acb5-52de-4a76-88c6-0eb844785025"},{"id":"c47d445d-a8c4-46a7-815e-584f4ff1b92b","company_id":"053355fc-0162-4bb9-b414-cbf7679ee9c8","title":"Research Scientist - Frontier Benchmarks","slug":"research-scientist-frontier-benchmarks-83166d4b","description":"About Snorkel \n At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.\n We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!\n \n \n ABOUT THE ROLE  \n We're looking for a Research Scientist to collaborate with partners and lead the development of the next frontier benchmarks and datasets. This is a highly visible, customer-facing role at the intersection of research, company strategy, and go-to-market. You'll design datasets taking into account frontier model performance and work with our academic partners, and then partner with delivery, product and go-to-market to scale out production. You will also  serve as a credible technical partner for our customers, prospects, and drive results that impact the broader research community. \n This role reports directly to the Head of Research and is ideal for someone who is energized by cross-functional work and wants to understand how startups operate across research, data operations, and commercial teams. \n MAIN RESPONSIBILITIES  \n \n Design state of the art datasets that drive frontier model training and evaluation based on current model performance and academic partnerships \n Translate benchmark insights into clear, compelling narratives that articulate the ROI of expert-curated data for customer-facing presentations, technical reports, and go-to-market materials.\n Work cross-functionally with data operations, product, engineering, and strategy to surface research findings that inform the company roadmap. \n Stay at the frontier of LLM evaluation research and bring best practices into Snorkel's workflows\n Represent Snorkel's research externally through publications, blog posts, conference talks, and customer engagements that advance the conversation around data-centric AI\n \n PREFERRED QUALIFICATIONS  \n \n Strong research background in AI/ML evaluation, NLP, or related fields, with a track record of rigorous experimental design — especially around measuring the impact of training and evaluation data on model behavior. \n Exceptional communication skills — able to present complex technical findings clearly to both technical and non-technical audiences \n Comfort operating in a fast-moving, cross-functional environment with ambiguous problem spaces \n Genuine interest in GTM strategy, startup dynamics, and the commercial side of AI data services. \n Ph.D. in machine learning, NLP, or a related field preferred; equivalent industry or research lab experience considered.\n \n \n  \n Salary Range \n $200,000 — $325,000 USD \n Be Your Best at Snorkel \n Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.\n Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. \n We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.","salary_min":200000,"salary_max":325000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["llm","generative-ai","nlp","research"],"apply_url":"https://job-boards.greenhouse.io/snorkelai/jobs/6009489004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T21:19:29Z","expires_at":"2026-06-29T14:03:05.663367Z","created_at":"2026-05-30T14:03:05.781019Z","updated_at":"2026-05-30T14:03:05.781019Z","company_name":"Snorkel AI","company_slug":"snorkel-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=snorkel.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/c47d445d-a8c4-46a7-815e-584f4ff1b92b"},{"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":"58a5e82c-4cbd-49e1-9ce2-45a7b213b0a9","company_id":"1df860e2-0800-48ea-81af-7121965be17a","title":"Engineering Manager - Machine Learning","slug":"engineering-manager-machine-learning-288c8ba8","description":"Your work will change lives. Including your own. \n \n The Impact You’ll Make \n You will lead a team working to build, scale, and optimize the machine learning infrastructure that powers Recursion's drug discovery platform. From model training pipelines to production deployment systems, to agent infrastructure and Large Language Models, you will ensure our ML models can operate at massive scale across our supercomputing infrastructure, both on prem and in the cloud. You will work cross-functionally across ML engineering, data science, and research teams to translate requirements into robust, scalable ML infrastructure solutions.\n In This Role You Will: \n \n Enable AI/ML, LLM, and Agentic Systems teams for scale - The ML infrastructure team is responsible for building and operating platforms that allow data scientists and ML engineers to train, deploy, and monitor models across Recursion's massive datasets. With billions of compounds, 30+ petabytes of experimental data, and complex deep learning workloads, your team enables everything from automated compound screening models to clinical trial prediction systems. You will work closely with researchers and ML engineers to understand their infrastructure needs and build scalable solutions for model development, training, and deployment.\n Act as a mentor, coach, and sponsor - You will share your technical, leadership and managerial skills in MLOps, distributed computing, and infrastructure engineering, delivering impact, learning, and growth across teams at Recursion. We believe that the best work comes from working across organizational boundaries and you will have opportunities to partner with ML research, platform engineering, and business teams.\n Enable a model-driven culture - Machine learning is at the core of everything we do. You will work with stakeholders across the business to ensure our ML infrastructure supports rapid experimentation, reliable model deployment, and continuous improvement. Problems you will work on could range from optimizing GPU cluster utilization to implementing Agentic orchestration and establishing company-wide MLOps standards\n \n The Team You’ll Join: \n You'll be part of a group of technical leaders who work together on the craft of engineering leadership as well as debate ML system architecture, MLOps patterns, and infrastructure optimization strategies. We all work better when we have the support of those around us and are learning together to solve complex problems around model scalability, deployment reliability, and infrastructure efficiency across our teams. You will report to the Executive Director of Engineering who broadly oversees Cloud Infrastructure, High Performance Compute and Machine Learning Infrastructure space.\n The Experience You Will Need: \n \n Experience in a hands-on technical role as a tech lead or a manager with a focus on infrastructure, MLOps and distributed systems. Excitement for deeply engaging in technical details with your team around machine learning, orchestration and agentic systems.\n A people-first mindset. We deliver in a way that prioritizes supporting our coworkers in their growth and experience and understand how Conway's Law shapes our ML system outcomes.\n Demonstrated past record of learning from and teaching peers in areas of ML infrastructure, model deployment, distributed compute, GPU optimization, and MLOps system architecture\n Excitement to learn parts of our ML tech stack that you might not already know. Our current ML infrastructure includes: Python, PyTorch, Docker, Kubernetes, Ray, Weights \u0026 Biases, Prefect, BigQuery, Postgres, GCP, CUDA, and various model serving frameworks.\n Fluency in life sciences or drug discovery is a plus but not required to be considered.\n \n Working Location \u0026 Compensation: \n This is an office-based, hybrid position at our US headquarters located in Salt Lake City, Utah . Employees are expected to work in the office at least 50% of the time.\n At Recursion, we believe that every employee should be compensated fairly. Based on the skill and level of experience required for this role, the estimated current annual base range for this role is $151,130 to $203,490 (USD) . You will also be eligible for an annual bonus and equity compensation, as well as a comprehensive benefits package. \n #LI-EP1\n The Values We Hope You Share: \n \n We act boldly with integrity. We are unconstrained in our thinking, take calculated risks, and push boundaries, but never at the expense of ethics, science, or trust. \n We care deeply and engage directly. Caring means holding a deep sense of responsibility and respect - showing up, speaking honestly, and taking action.\n We learn actively and adapt rapidly. Progress comes from doing. We experiment, test, and refine, embracing iteration over perfection.\n We move with urgency because patients are waiting. Speed isn’t about rushing but about moving the needle every day.\n We take ownership and accountability. Through ownership and acco","salary_min":151130,"salary_max":203490,"location":"Salt Lake City, Utah","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["pytorch","deep-learning","cloud","mlops","gpu","llm","distributed-systems","healthcare"],"apply_url":"https://job-boards.greenhouse.io/recursionpharmaceuticals/jobs/7961460","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T14:56:13Z","expires_at":"2026-06-29T14:07:04.532978Z","created_at":"2026-05-30T14:07:04.642889Z","updated_at":"2026-05-30T14:07:04.642889Z","company_name":"Recursion","company_slug":"recursion","company_logo_url":"https://www.google.com/s2/favicons?domain=recursion.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/58a5e82c-4cbd-49e1-9ce2-45a7b213b0a9"},{"id":"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"}],"page":1,"per_page":20,"total":2636,"total_pages":132}