{"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":"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":"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":"a702d67f-523f-4f26-a10d-c872f90afda6","company_id":"b6e5a3d1-9bde-4a82-8d78-9f38ed99ee81","title":"Staff Applied Scientist - Agentic Interfaces","slug":"staff-applied-scientist-agentic-interfaces-72926417","description":"Team description \n At Datadog, AI agents are becoming first-class consumers of observability, security, and software delivery data — from third-party coding agents like Claude Code, Cursor, and Copilot, to our own Bits SRE, Bits Assistant, and Bits Dev Agent. The Agentic Interfaces team owns the platform that connects these agents to Datadog: the MCP Server, the tools and retrieval surfaces agents call into, and — critically — the evaluation systems that tell us whether an agent's experience on Datadog data is actually getting better over time.\n This role is about that last piece. We're hiring a Staff Applied Scientist to define what \"good\" means for an Agentic interface at Datadog and to build the measurement systems that make it true. \"Good\" isn't one number — it spans answer quality, tool-selection accuracy, retrieval relevance, latency, token cost, and end-to-end agent success on real customer workflows. You'll design the evals, build the datasets, define the metrics, and partner with the AI engineers on the team to land the platform that lets every product group at Datadog ship integrations that are demonstrably better release over release.\n The space is full of open research questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when the tool catalog has hundreds of entries and grows weekly? How do you build a measurement system that catches regressions across first-party and third-party agents at once, without each team writing their own harness? If those are the problems you want to spend your time on, come build this with us.\n Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. \n  \n What You’ll Do: \n \n \n Own the evaluation strategy for Datadog's AI agent integrations. Define the metrics — offline and online, quality and cost, single-turn and trajectory-level — that the team and the broader organization optimize against.\n \n Build the eval datasets, golden traces, and regression harnesses that catch quality changes before they hit customers, and make those assets reusable by every team contributing tools to the platform.\n \n Drive measurable improvements to retrieval relevance, tool-selection accuracy, and context efficiency, partnering closely with the AI engineers on the team who build the underlying platform.\n \n Run applied research on the open problems in agent–data interaction: tool selection under large catalogs, multi-turn agent evaluation, grounding and hallucination control on live telemetry, cost/quality tradeoffs at scale.\n \n Partner with the Bits SRE, Bits Assistant, and Bits Dev Agent teams so first-party agents benefit from the same measurement substrate as third-party integrations, and so learnings move freely in both directions.\n \n Provide technical leadership across the Agentic Interfaces team and the broader organization through design reviews, working groups, and mentorship, and represent the team externally through talks, blog posts, and contributions to the open agent ecosystem.\n \n Who You Are: \n \n \n You have a BS/MS/PhD in a scientific field, or equivalent experience.\n \n 10+ years of relevant engineering or applied science experience, including time as a technical lead.\n \n Proven track record of leading ML or GenAI initiatives in a product-driven environment, from research through production.\n \n Significant experience with evaluation, experimentation, or measurement of ML systems at scale.\n \n You bring a strong product mindset and are comfortable driving initiatives across cross-functional teams.\n \n You thrive in ambiguity and can make sound technical calls when the path isn’t yet defined.\n \n Benefits and Growth: \n \n \n New hire stock equity (RSUs) and employee stock purchase plan (ESPP)\n \n Continuous professional development, product training, and career pathing\n \n An inclusive company culture, giving programs, and the ability to join our Community Guilds (Datadog employee resource groups)\n Competitive global benefits and global Spring Health benefits for employees and dependents age 6+\n \n #LI-Onsite\n Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.\n The reasonably estimated yearly salary for this role at Datadog is:\n $276,000 — $345,000 USD \n \n About Datadog:  \n Datadog is the leading observability and security platform for the AI era, providing businesses with ","salary_min":276000,"salary_max":345000,"location":"New York, NY","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["healthcare","agents","generative-ai","code-generation"],"apply_url":"https://careers.datadoghq.com/detail/7964141/?gh_jid=7964141","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T14:06:44Z","expires_at":"2026-06-29T14:03:24.031594Z","created_at":"2026-05-29T14:09:23.831464Z","updated_at":"2026-05-30T14:03:24.142868Z","company_name":"Datadog","company_slug":"datadog","company_logo_url":"https://www.google.com/s2/favicons?domain=datadoghq.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a702d67f-523f-4f26-a10d-c872f90afda6"},{"id":"960ff8ca-6a38-4ffc-893e-dd306a5479c9","company_id":"1c5cd464-c475-4739-a226-7268fa45343a","title":"Digital Customer Programs Manager","slug":"digital-customer-programs-manager-06d80811","description":"ABOUT ASSEMBLED\n\nGreat customer support requires human agents and AI in perfect balance, and Assembled https://www.assembled.com/customers is the only unified platform that orchestrates both at scale. Companies like Canva, Etsy, and Robinhood use Assembled to coordinate their entire support operation — in-house agents, BPOs, and AI — in a single operating system. With AI Agents that resolve cases end-to-end, AI Copilot for agent assistance, and AI-powered workforce management that optimizes both human and AI capacity, Assembled helps teams deliver faster, better service while making smarter decisions about how to staff and automate. Backed by $71M from NEA, Emergence Capital, and Stripe, we're building the platform that makes AI and human collaboration actually work.\n\n\n\n\nTHE ROLE\n\nThe Digital Customer Programs Manager owns Assembled's Scale tier customer experience. The Scale tier is served through structured programs: self-serve resources, community engagement, and light-touch human interaction — not an assigned CSM relationship. This role sits in the Support org, within our broader Customer Experience department, and that's intentional. When customers hit technical friction, the response needs to be as disciplined as it is empathetic. You'll move fluidly between customer success instincts and technical support process rigor, with impact measured across the entire tier, not a single account list.\n\n\n\nYou'll be the primary executor of the Scale Experience program — high daily volume, a wide range of customer maturity levels, and constant context-switching. If you're energized by breadth and by building things that scale, this is your role.\n\n\n\n\nRESPONSIBILITIES\n\n - Account Health Monitoring — Own or help build the systematic mechanism for tracking health signals across the tier. Know which accounts are engaged, which are drifting, and why. Engage when signals change — don't wait for a renewal to address misalignments.\n\n - Renewals — Proactively manage the renewal motion for this tier, using health data to get ahead of risk well before renewal dates. Facilitate pre-renewal check-ins for accounts showing growth potential or as needed to address questions on terms, value, legal or contract details.\n\n - Office Hours — Staff scheduled 1:1 sessions for Scale customers alongside the support team, tag-teaming with support engineers based on the account and nature of the request. Sessions cover product questions, troubleshooting, and relationship or commercial topics. Log contact drivers to inform knowledge base priorities and product feedback.\n\n - Community \u0026 Engagement — Own Assembled's customer community presence across channels and formats. This may include digital community platforms, webinars, events, forums, the Assembled Slack community, or other programming. Moderate discussions, respond to questions, surface relevant resources, and identify accounts with high potential or in need of additional support.\n\n - Customer Feedback \u0026 Surveys — Own the survey cadence for the Scale tier: design, send, monitor response rates, synthesize results, and surface themes to leadership. Partner with cross-functional owners of survey tooling to coordinate timing and ensure results are actioned across the customer experience.\n\n - Tier Upgrade Flagging — When a Scale customer's needs or growth trajectory warrant a commercial conversation, you own identifying it and routing it appropriately. You're protecting the model, not just the relationship.\n\n - Support Integration — Work hand-in-hand with support engineering across all customer touch points. File tickets, triage issues, own communication on escalations, and respect established support workflows. You're not a support engineer, but you operate like someone who understands why process discipline makes the whole system work.\n\nYou'll know you're succeeding when Scale tier churn is low, renewal rates are healthy, and CSAT and NPS for this segment are at or above industry benchmarks.\n\n\n\n\nABOUT YOU\n\n - You know what it feels like to be on the other side of a scale tier experience. You've been in the weeds of customer-facing work and you bring that empathy into every interaction. You understand the world of support professionals and what good actually looks like to them.\n\n - You've been in a high-volume customer-facing role. You've managed more accounts than you could possibly give individual attention to, and you figured out how to make that work. You understand the difference between a customer who needs more of your time and a customer who needs better resources.\n\n - You hold the line without losing the relationship. When a customer asks for a dedicated CSM, a custom QBR, or a direct line to engineering, you know how to reset expectations in a way that leaves them feeling heard rather than rejected. You've had hard renewal conversations and didn't spiral.\n\n - You respect the power of process. You file the ticket and set expectations (internally \u0026 externally","salary_min":120000,"salary_max":150000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"junior","tags":["agents","llm","code-generation","payments"],"apply_url":"https://jobs.ashbyhq.com/assembledhq/66164c16-1b36-498d-a9d5-7e34ad543d2f/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T05:50:42.725Z","expires_at":"2026-06-29T14:12:01.005639Z","created_at":"2026-05-29T14:47:55.874652Z","updated_at":"2026-05-30T14:12:01.117957Z","company_name":"Assembled","company_slug":"assembled","company_logo_url":"https://www.google.com/s2/favicons?domain=assembled.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/960ff8ca-6a38-4ffc-893e-dd306a5479c9"},{"id":"a1e6623a-57bb-42a8-964e-e2b9698f0e35","company_id":"e455f75a-a424-4955-9844-afebe8ea6eb4","title":"Senior Forward Deployed Engineer","slug":"senior-forward-deployed-engineer-ff299cc4","description":"Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.\n About Okta for AI Agents \n Okta secures access for 20,000 organizations and billions of users. Okta for AI Agents extends that work to the agentic shift. Deploying an AI agent is not like deploying traditional software. You are putting professional work output into production, and it needs deep integration, continuous tuning, and change management. Every agent needs an identity, a scope, an audit trail, and a way to be shut down when it goes wrong. Most enterprises have not built this yet. We are.\n We hire builders who see the cracks in enterprise agent identity that everyone else has learned to live with.\n The Role \n You embed inside four to five of Okta’s most strategic enterprise customers as their dedicated technical partner for agent identity. You sit alongside their identity, platform, and security engineering teams, write production code in their environment, and own the technical outcome from prototype through production.\n You are a builder-consultant. You go past architecture diagrams to code, debug, and ship bespoke agent identity solutions inside the customer’s environment. You ship secure agents faster for the customer, and you feed real field insight back to Okta product engineering.\n Responsibilities \n \n Become the customer’s trusted technical voice on agent security. Sit in their standups, design reviews, and incident response. Earn a seat on their architecture review board and security council for agent risk decisions.\n Architect and deploy with the customer’s team. Build Okta’s agent security stack into their infrastructure: Cross-App Access (XAA), Fine-Grained Authorization (FGA), MCP Gateway, and agent client registration. Own the identity, delegation, audit, and kill-switch architecture end to end, and coach their engineers on the patterns.\n Engage senior leadership. Brief the CISO, CIO, identity leaders, Chief AI Officer, and principal architects. Translate token-exchange flows into board-level agent risk, and AI governance mandates into architecture.\n Deliver white-glove deployment. Agents in production with full identity coverage, security review passed, governance requirements met, and posture visibility online. The customer points to you as the reason their agent program is real.\n Keep deployments defensible. Align architecture decisions to OWASP Top 10 for Agentic Applications, NIST AI RMF, and MITRE ATLAS, and to HIPAA, FedRAMP, or SOC 2 where the customer is regulated.\n Wire Okta into the customer’s stack. Connect O4AA to their IdP for human-to-agent links, IGA for agent lifecycle, ISPM for posture, SIEM and EDR for behavior coverage, and policy engines for runtime decisions.\n Build evals and observability. Authorization decision latency, scope sprawl across agents, anomalous delegation chains, audit completeness, kill-switch verification, and rogue agent detection.\n Turn field patterns into product. Extract the recurring gaps from their architects and governance leads, and convert them into reusable modules and roadmap fixes that ship for every other customer.\n Be on site. Regular presence at customer locations. Trust and governance alignment happen in the room.\n \n Requirements \n \n Engineering pedigree. 7+ years shipping production software, still hands-on in the IDE, with on-call experience and operational maturity in systems that authenticate and authorize at high throughput.\n Identity protocols. OAuth 2.0, OIDC, SAML, SCIM, RFC 8693 token exchange, act claims, CIMD and DCR, DPoP.\n Agent security frameworks. Working knowledge of OWASP Top 10 for Agentic Applications, NIST AI RMF, and MITRE ATLAS. Familiarity with MCP, A2A, ISO/IEC 42001, and the EU AI Act. Comfortable mapping deployments to HIPAA, FedRAMP, and SOC 2.\n Fine-grained authorization. ReBAC and ABAC with policy engines (OPA, Cedar, OpenFGA, or equivalent), and a working understanding of how agents acquire tokens, call APIs, and delegate.\n AI hands-on. Built production integrations with Claude, ChatGPT, Microsoft Copilot, Agentforce, Bedrock, LangChain, CrewAI, the OpenAI Agents SDK, or MCP servers.\n AI-native development. Daily use of Claude Code, Cursor, GitHub Copilot, or equivalent.\n Customer-facing range. At home in a customer standup and a CISO briefing on the same day. You build trust with senior engineering leaders and you stay in the room when their internal politics get sharp.\n High agency, founder’s mindset. A zero-to-one self-starter who owns outcomes end to end.\n \n #LI-Remote\n P25","salary_min":200000,"salary_max":275000,"location":"Bellevue, WA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["fine-tuning","code-generation","agents","cloud","security"],"apply_url":"https://www.okta.com/company/careers/opportunity/7961356?gh_jid=7961356","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T13:23:38Z","expires_at":"2026-06-29T14:09:00.148157Z","created_at":"2026-05-28T14:10:39.406925Z","updated_at":"2026-05-30T14:09:00.25852Z","company_name":"Okta","company_slug":"okta","company_logo_url":"https://www.google.com/s2/favicons?domain=okta.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a1e6623a-57bb-42a8-964e-e2b9698f0e35"},{"id":"d8372e30-6a66-49c1-b225-3271b0a4a19f","company_id":"a4de8095-cb98-4b8b-9bfc-c2d248f257ea","title":"Senior Staff Security Engineer, AI","slug":"senior-staff-security-engineer-ai-5fc21c61","description":"At Ripple, we’re building a world where value moves like information does today. It’s big, it’s bold, and we’re already doing it. Through our crypto solutions for financial institutions, businesses, governments and developers, we are improving the global financial system and creating greater economic fairness and opportunity for more people, in more places around the world. And we get to do the best work of our career and grow our skills surrounded by colleagues who have our backs.  \n If you’re ready to see your impact and unlock incredible career growth opportunities, join us, and build real world value. \n \n THE WORK: \n As a Senior Staff Security Engineer focused on AI Security, you will be Ripple's deepest technical expert at the intersection of artificial intelligence and security. This is a purpose-built, high-impact individual contributor role that spans two critical mandates: securing AI systems that Ripple builds and operates, and harnessing AI to make Ripple's security function faster, smarter, and more scalable.\n You will lead the technical strategy for AI security across the agentic SDLC, define and operationalize guardrails for LLM and agentic AI adoption, and build AI-powered security tooling in close partnership with the broader organization to embed AI security into how Ripple operates every day. You will also shape Ripple's external posture on AI security, contributing to industry standards, regulatory discussions, and Ripple's published security practices.\n WHAT YOU’LL DO: \n \n Drive the AI Security technical strategy and roadmap, defining how Ripple secures its AI systems, governs agentic workflows, and embeds security controls into the AI development lifecycle from day one.\n Design and implement security controls for LLM-integrated and agentic AI systems, including sandboxing, identity and permission scoping, runtime monitoring, and containment of autonomous agent actions that exceed authorized scope.\n Own AI security across the Controlled Agentic SDLC, establishing security guardrails, AI provenance standards, dual-review requirements, and audit trail controls for AI-assisted development across Ripple Engineering.\n Lead the security review and risk assessment of all AI integrations entering production, including LLM APIs, SaaS copilots, AI code editors, agentic workflows, third-party MCP servers, and vendor-embedded AI.\n Build and scale Ripple's Shadow AI detection capability, surfacing unsanctioned AI usage, driving adoption of the AI acceptable use policy, and ensuring all AI workflows operate within Ripple's auditable perimeter.\n Serve as Ripple's go-to technical resource on agentic AI risks, including MCP server security, tool poisoning, prompt injection at the orchestration layer, and excessive agency in multi-agent systems, translating emerging threats into concrete mitigations with Engineering and Product.\n Shape Ripple's external AI security posture, contributing to industry frameworks, engaging regulators, and publishing research that establishes Ripple as a credible voice in responsible AI security. \n \n \n WHAT YOU'LL BRING:  \n \n \n 10+ years of Security Engineering experience with demonstrated depth in at least two domains, such as Product Security, Cloud Security, or Security Operations, and meaningful hands-on exposure to AI or ML security in practice.\n Solid understanding of AI and LLM security concepts, including prompt injection, jailbreaks, data poisoning, model extraction, RAG manipulation, and agentic risks such as tool poisoning, excessive agency, and MCP server vulnerabilities.\n Experience securing agentic AI systems, including sandboxing, permission scoping, human-in-the-loop design, or runtime monitoring for autonomous workflows.\n Fluency with core Security Engineering domains including cloud security on AWS, GCP, or Azure, CI/CD pipeline security, container and Kubernetes security, IAM, and API security, with the ability to reason about how these apply in AI-specific contexts.\n Strong threat modeling instincts, whether using STRIDE, MITRE ATLAS, OWASP LLM Top 10, or your own approach, and comfort applying frameworks to architectures where the playbook remains in development.\n Experience in FinTech, crypto, or other highly regulated environments is a strong plus, ideally with exposure to frameworks like NYDFS, MAS, DORA, or SOC 2 as they relate to AI adoption.\n Proven ability to work across teams, influence technical direction without direct authority, and bring structure to problems that span Engineering, Product, and Security.\n A genuine builder's mentality. You are energized by problems without established playbooks, comfortable building in ambiguity, and motivated by raising the bar in an area that is still being defined.\n \n Other common names for this role: AI Security Architect, LLM Security Engineer, Agentic AI Security Lead \n For positions that will be based in CA, the annual salary range for this position is below. Actual salaries may vary based","salary_min":232000,"salary_max":290000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["llm","healthcare","payments","rag","code-generation","agents","security"],"apply_url":"https://ripple.com/careers/all-jobs/job/7961902?gh_jid=7961902","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T13:13:15Z","expires_at":"2026-06-29T14:12:02.752999Z","created_at":"2026-05-28T14:13:53.327797Z","updated_at":"2026-05-30T14:12:02.874002Z","company_name":"Ripple","company_slug":"ripple","company_logo_url":"https://www.google.com/s2/favicons?domain=ripple.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d8372e30-6a66-49c1-b225-3271b0a4a19f"},{"id":"a4876350-3ed0-4a94-bdd6-aeee75b595c0","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Platform Engineer, AI Tooling","slug":"platform-engineer-ai-tooling-ce70c405","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\nThe Platform Engineer, AI Tooling on the Developer Experience Team (part of Foundation Engineering group) will help build the internal AI platform that makes Drata's engineers more efficient - the tools, agents, and integrations that turn AI coding agents (and the rest of the AI dev stack) into the default way work gets done at Drata. This is not a product-AI role - you're not building AI features for Drata's customers. You're building for Drata's engineers: MCP servers that connect AI agents to our internal systems, custom agent skills and subagents tuned to specific workflows, agentic workflows that automate code generation, verification, testing, and delivery, and the observability and cost controls behind all of it. Your \"customer\" is not Drata's normal users, it's Drata's engineers.\n\nYou'll own meaningful pieces of the platform, work closely with senior engineers, and ramp fast in a space that's still being defined. You'll participate in design, coding, testing, and production release, and deliver code in an agile team environment.\n\nWhat you’ll do:\n\n - Implement custom agent skills, subagents, hooks, and plugins for specific engineering workflows (PR review, test generation, on-call summaries, migration scripts, release notes)\n\n - Build agentic workflows that automate parts of the coding lifecycle: code generation, verification, testing, and delivery - agents that take a ticket and turn it into a tested, reviewable PR\n\n - Help engineering teams adopt and customize AI coding tools: pair with them on prompts, debug agents that misbehave, ship the skill that solves their actual problem\n\n - Wire AI into CI/CD: automated PR review, doc generation, test scaffolding, bug triage\n\n - Build the observability layer: usage telemetry, cost dashboards, audit logs for AI-driven changes\n\n - Design and run evaluations for agent workflows\n\n - Maintain engineering harness that the org reuses across teams\n\n - Investigate and fix issues: misbehaving agents, eval regressions, cost spikes, permission edge cases in MCP servers\n\n - Participate in design reviews, post-mortems, and on-call for the AI Tooling platform\n\n - Write reusable, testable, and efficient code\n\n - Stay current with new AI coding tools and patterns, and bring back what's useful\n\n - Research and train on technologies you think may be appropriate for current or future projects\n\nWhat you’ll bring:\n\n - 3+ years of experience as a software engineer building production systems and plat","salary_min":131900,"salary_max":178500,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"mid","tags":["agents","api-design","healthcare","code-generation","platform"],"apply_url":"https://jobs.ashbyhq.com/drata/3b1adc01-87ac-45ae-b50b-4de5597e41a7/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:24:49.409Z","expires_at":"2026-06-29T14:13:57.011821Z","created_at":"2026-05-27T14:14:33.02715Z","updated_at":"2026-05-30T14:13:57.121907Z","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/a4876350-3ed0-4a94-bdd6-aeee75b595c0"},{"id":"f3c01abc-b194-443a-bdbf-d93481003d55","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Senior Platform Engineer 2, AI Tooling","slug":"senior-platform-engineer-2-ai-tooling-c4e857a7","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\nThe Senior Platform Engineer II, AI Tooling on the Developer Experience Team (part of Foundation Engineering group) will lead the design and delivery of the internal AI platform that makes Drata's engineers more efficient - the tools, agents, and integrations that turn AI coding agents (and the rest of the AI dev stack) into a paved road for everyday engineering work. This is not a product-AI role - you're not building AI features for Drata's customers. You're building for Drata's engineers: MCP servers that connect AI agents to our internal systems, custom agent skills and subagents tuned to how Drata works, agentic workflows that automate the engineering lifecycle end-to-end (code generation, verification, testing, delivery), and the governance, observability, and cost controls that keep all of it safe and accountable.\n\nYour \"customer\" is not Drata's normal users, it's Drata's engineers. The work is measured upstream of every PR: shorter cycle time, less toil, fewer mistakes, faster onboarding, more time on the work that matters. You'll set technical direction, mentor engineers, and make the architecture calls that shape how AI shows up in every engineering workflow at Drata.\n\nWhat you’ll do:\n\n - Architect the internal AI platform: MCP servers, agent customizations, agentic workflows, engineering harness, and integrations that make AI the default way engineers get work done at Drata\n\n - Design and ship custom agent skills, subagents, hooks, and plugins tuned to specific engineering workflows (code review, test generation, PR triage, on-call, release notes, migrations)\n\n - Build end-to-end agentic workflows that automate code generation, verification, testing, and delivery: agents that pick up a ticket, write the code, run the tests, and ship the PR\n\n - Design async, recoverable, long-running agent workflows - Temporal is already in our stack and is a natural substrate for agents that run for minutes or hours and have to survive restarts\n\n - Lead the rollout and customization of AI coding tools across the org\n\n - Wire AI into CI/CD: automated PR review, test generation, doc generation, migration agents, bug triage agents, autonomous coding agents in pipelines\n\n - Build the governance layer: usage telemetry, cost tracking, audit trails, security policy enforcement (what code can leave the org boundary, secrets scrubbing, prompt injection defenses inside the repositories)\n\n - Design and run evals that tell us which PR review prompt","salary_min":174500,"salary_max":236100,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["agents","healthcare","code-generation","llm","platform"],"apply_url":"https://jobs.ashbyhq.com/drata/3f52dbee-ddf8-48f5-ac15-9dc04b588348/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:23:56.424Z","expires_at":"2026-06-29T14:13:56.93483Z","created_at":"2026-05-27T14:14:32.938355Z","updated_at":"2026-05-30T14:13:57.045075Z","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/f3c01abc-b194-443a-bdbf-d93481003d55"},{"id":"4890fceb-0740-4c18-9993-bac00340d94c","company_id":"dcf03132-cd3a-4108-8e1d-20ab36008ea2","title":"Generative AI Engineer","slug":"generative-ai-engineer-eb00890a","description":"Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams design and operate analytics, machine learning, and AI agents with the transparency, collaboration, and control enterprises require. Sitting above data platforms, cloud infrastructure, and AI services, Dataiku connects the full enterprise AI stack — empowering organizations to run AI across multi-vendor environments with centralized governance. The world’s leading companies rely on Dataiku to operationalize AI and run it as a true business performance engine delivering measurable value. For more, visit the Dataiku blog , LinkedIn , X , and YouTube .\n As a Generative AI Engineer on the ED\u0026A team, you will build the agentic AI systems that change how Dataiku runs internally. The role is hands-on and end-to-end: you’ll work close to the business, turn real problems into working software, and see your solutions through from first conversation to production.\n This position can be based in our New York office or remotely within the Eastern Time Zone. \n How You'll Make an Impact\n Agentic AI Solution Development \u0026 Integration\n Design end-to-end AI solutions on Dataiku's platform, leveraging Dataiku Agent Hub, Prompt Studio, LLM Mesh, and Knowledge Banks (Vector Stores), or Python-based frameworks where needed.\n Build and orchestrate multi-agent systems using Dataiku's Visual Agents (simple and structured), as well as code-based frameworks (LangGraph, CrewAI, Claude Agent SDK, OpenAI Agents SDK) as appropriate.\n Integrate and optimize LLM APIs across providers (OpenAI, Anthropic, Google Gemini, AWS Bedrock, Azure, open-source models via Dataiku's LLM Mesh), applying model routing strategies to balance cost, latency, and quality.\n Implement Retrieval-Augmented Generation (RAG) pipelines, including agentic RAG and GraphRAG, using Dataiku's Knowledge Banks with reranking, dynamic filtering, and document extraction capabilities.\n Stakeholder Engagement \u0026 Delivery\n Work exclusively with the Marketing organisation, partnering across functions such as Demand Generation, Content Marketing, Product Marketing, Field Marketing, Marketing Operations, Brand, and Communications.\n Engage marketing stakeholders to gather business requirements, then go further: identify the underlying user or team pain points those requirements represent, and design solutions that address both the stated need and the deeper problem.\n Own projects end-to-end, from requirements intake and solution design through to build, deployment, and handover.\n Agent \u0026 Tool Development\n Develop autonomous and semi-autonomous AI agents, using Dataiku's Agent Builder, custom Python-based architectures (LangGraph, CrewAI, Claude Agent SDK, etc.), or a combination of both. Exercise judgment on when to leverage platform capabilities and when to build custom solutions.\n Design and build Agent Tools beyond documented examples, including custom API integrations, data retrieval modules, decisioning logic, and automated workflows, pushing past out-of-the-box patterns to deliver solutions tailored to specific business problems.\n Build, publish, and consume MCP (Model Context Protocol) servers to enable agent-to-tool integration across systems, including designing custom MCP servers where needed.\n Develop evaluation and monitoring approaches for agent systems, combining Dataiku's built-in capabilities with custom instrumentation to measure reliability, accuracy, cost, and business impact in production.\n AI Governance \u0026 Evaluation\n Design and maintain evaluation frameworks (evals) for LLM-based systems, measuring accuracy, latency, cost, and reliability in production.\n Adhere to data governance, security, and regulatory compliance requirements (EU AI Act awareness, responsible AI practices) for all AI solutions.\n Leverage Dataiku's Cost Guard and Quality Guard features to manage LLM spend, enforce usage policies, and maintain output quality standards.\n Work closely with analytics and data engineering teams to maintain metadata on reference datasets for LLM consumption.\n Web Application Development\n Create front-end user interfaces for AI applications using HTML, CSS, and JavaScript, within Dataiku's webapps framework, Dataiku Answers for chat-based interfaces, or standalone applications built with Vue.js and Node.js.\n Collaborate on UX design, ensuring internal stakeholders find AI solutions intuitive and responsive.\n Continuous Learning\n Provide product feedback to the development team to improve the platform.\n Stay current with the rapidly evolving AI engineering landscape, agent frameworks, model capabilities, evaluation practices, governance requirements, and tools like MCP and A2A protocols.\n  \n What You'll Need to Be Successful\n Technical Proficiency\n Must have strong Python skills (including familiarity with typical data science and AI engineering libraries).\n Must have hands-on experience building agentic AI systems","salary_min":160000,"salary_max":240000,"location":"New York, NY","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["rag","generative-ai","llm","payments","code-generation","embeddings","cloud","agents"],"apply_url":"https://job-boards.greenhouse.io/dataiku/jobs/6002762004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-25T21:07:05Z","expires_at":"2026-06-29T14:08:05.896911Z","created_at":"2026-05-27T14:08:19.988934Z","updated_at":"2026-05-30T14:08:06.020687Z","company_name":"Dataiku","company_slug":"dataiku","company_logo_url":"https://www.google.com/s2/favicons?domain=dataiku.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4890fceb-0740-4c18-9993-bac00340d94c"},{"id":"d134135d-62d9-4aa9-acb7-410bbd77911c","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Sr. Staff Machine Learning Engineer, Content Ecosystem","slug":"sr-staff-machine-learning-engineer-content-ecosystem-3ffaf377","description":"About Pinterest: \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .\n Pinterest works when the content ecosystem works: when people can reliably find ideas that feel inspiring, trustworthy, and actionable—and when the ecosystem continuously learns what to create, surface, and sustain next. In this Sr. Staff ML Engineer role, you’ll be the technical lead shaping how Pinterest understands and improves its content as a living marketplace: a dynamic system with feedback loops between users, creators/publishers, distribution, and long-term business outcomes.\n You will define a durable ML strategy that goes beyond “engagement metrics” to improve overall ecosystem health—identifying where we’re underserving content, uncovering the attributes that make content succeed, and designing optimization approaches that balance relevance, quality, diversity, integrity, and monetization. The problems are inherently multi-objective and long-horizon: the best decisions today should strengthen the ecosystem tomorrow. If you’re excited by high-leverage technical leadership, rigorous ML thinking, and marketplace-style dynamics at scale, this role offers a chance to directly shape Pinterest’s moat and the experience millions of people come to for ideas they can act on.\n What you’ll do: \n \n Set technical strategy and vision for ML systems that improve the end-to-end content ecosystem, including supply, distribution, and engagement/utility outcomes.\n Partner with DS teams to develop a content ecosystem measurement framework to quantify content health and performance (e.g., content quality, freshness, diversity, coverage, creator/content sustainability, and user value), and align it with company/business goals.\n Identify and close content gaps by building models and insights that answer: what content is missing, for whom, in which contexts, and why.\n Deeply understand what content works and why by combining causal thinking, experimentation, and model interpretability to connect content attributes and distribution mechanisms to downstream user and business outcomes.\n Build and optimize content marketplace mechanisms that balance multi-sided incentives and constraints (e.g., users, creators/publishers, advertisers, internal policy/safety), while maximizing long-term ecosystem value.\n Design multi-objective optimization approaches that manage tradeoffs across relevance, quality, diversity, creator incentives, integrity/safety, and monetization.\n Partner closely with cross-functional teams (Product, Data Science, UX Research, Content/Creator teams, Trust \u0026 Safety, Ads, Infra) to translate ambiguous ecosystem problems into clear technical roadmaps and deliver measurable impact.\n Mentor and grow junior ML engineers through technical coaching, design reviews, career development support, and creating a culture of strong engineering and scientific rigor.\n Raise the quality bar for ML engineering by establishing best practices for data quality, model governance, reliability, privacy-aware design, and operational excellence.\n Communicate clearly and influence broadly by producing crisp technical proposals, aligning stakeholders on tradeoffs, and driving decisions across org boundaries.\n Explore and apply advanced methods where beneficial—e.g., game-theoretic approaches, reinforcement learning, mechanism design, or bandit-style optimization—to improve marketplace dynamics and long-term ecosystem outcomes.\n \n What we’re looking for: \n \n Strong fundamentals in machine learning and optimization, with the ability to apply them to real-world, high-scale ecosystem problems.\n Demonstrated ability to lead technical strategy, navigate ambiguity, and deliver end-to-end impact.\n Deep interest in marketplace dynamics (multi-sided incentives, feedback loops, long-term health metrics), and comfort with multi-objective tradeoffs.\n Experience with Cursor, Copilot, Codex, or","salary_min":227871,"salary_max":469147,"location":"San Francisco, CA","workplace":"remote","job_type":"full-time","experience_level":"lead","tags":["fine-tuning","code-generation","reinforcement-learning","llm","machine-learning"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=7919043","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-22T21:44:36Z","expires_at":"2026-06-29T14:08:27.825754Z","created_at":"2026-05-27T14:08:41.489689Z","updated_at":"2026-05-30T14:08:27.939307Z","company_name":"Pinterest","company_slug":"pinterest","company_logo_url":"https://www.google.com/s2/favicons?domain=www.pinterest.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d134135d-62d9-4aa9-acb7-410bbd77911c"},{"id":"4ec47e11-41e8-4449-b012-74d40f99df46","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Staff Machine Learning Engineer, Ads Conversion","slug":"staff-machine-learning-engineer-ads-conversion-06f85a08","description":"About Pinterest: \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .\n We are looking for a Staff MLE to lead the technical vision for our Ads Advanced Conversion Modeling team, building the state-of-the-art systems that power our global marketplace.\n  \n What you’ll do:  \n \n Lead the technical direction and development of state-of-the-art applied ML projects for ads conversion.  \n Design and build large-scale DNN models to improve user action prediction with low latency.  \n Mine text, visual, and user signals to better understand intention and infer interests from online activity.  \n Use AI to accelerate analysis and iteration, while applying judgment and verification to ensure correctness and quality.  \n Automate repeatable tasks such as documentation, reporting, and QA checks to speed up the development lifecycle.  \n Coach and mentor engineers while collaborating with product and sales to design new ad products.\n \n  \n What we’re looking for: \n \n Degree in Computer Science, Statistics, or a related field.  \n 6+ years of industry experience building production ML systems at scale (Search, Recommendations, or Ranking).  \n 2+ years of experience leading technical projects or teams.  \n Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs.  \n Experience with Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring.\n Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration.\n High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final deliverables.\n Strong mathematical foundation and experience with statistical methods and A/B testing. \n \n  \n Relocation Statement:  \n \n This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.\n \n  \n In-Office Requirement Statement: \n \n We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.\n This role will need to be in the office for in-person collaboration 1-2 times every 6 months and therefore can be situated anywhere in the country.\n \n  \n #LI-SM4\n #LI-REMOTE\n At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.\n Information regarding the culture at Pinterest and benefits available for this position can be found here . \n US based applicants only\n $222,716 — $389,753 USD \n Our Commitment to Inclusion: \n Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete  this form  fo","salary_min":222716,"salary_max":389753,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["fine-tuning","llm","code-generation","machine-learning"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=7902034","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-22T19:35:37Z","expires_at":"2026-06-29T14:08:28.182671Z","created_at":"2026-05-27T14:08:41.839976Z","updated_at":"2026-05-30T14:08:28.299621Z","company_name":"Pinterest","company_slug":"pinterest","company_logo_url":"https://www.google.com/s2/favicons?domain=www.pinterest.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4ec47e11-41e8-4449-b012-74d40f99df46"},{"id":"f2e1438f-11be-4b9b-a71c-550e78f26436","company_id":"19955a21-2cd6-41fd-a4a8-19b7a942ac16","title":"Senior Value Engineer","slug":"senior-value-engineer-5f38b6e0","description":"Celonis is the global leader in Process Intelligence and the pioneer of Process Mining technology. As one of the world’s fastest-growing enterprise SaaS companies, we are changemakers pushing the boundaries of what’s possible. We invest heavily in advanced AI capabilities—specifically our Process Intelligence Graph—to turn data insights into immediate business action. We believe there is a massive opportunity to unlock global productivity and sustainability by placing intelligence at the core of every business process. Join our mission to make processes work for people, companies, and the planet.\n The Role: \n As a Value Engineer, you are spearheading our mission of solving critical operational challenges for enterprise customers. You will be working with strategic clients to understand their unique objectives, from modernizing legacy systems to optimizing finance processes and deploying an agentic business. In partnership with the Celonis Sales Teams, you have full responsibility for the end-to-end value journey of our customers. You are our customers' trusted advisor and help them drive adoption and realize measurable business value using Celonis.\n You can expect to blend process and industry expertise with a solution-first mindset, analyzing customer data and deploying tactical solutions. By using the Celonis Process Intelligence platform to feed critical operational context to AI and LLM tools, you will help our customers move past simple automation to deploy intelligent, autonomous agents that solve complex business bottlenecks. You’re the Celonis expert, connecting the dots between their pain points and how our platform can solve the problem. You’d be managing weekly cadences, QBRs, and value plans to demonstrate the value of our solutions to VP+ level executives.\n Key Responsibilities: \n \n Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the pre-sales expansion cycles and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds are successfully met.\n Insights framing and value realization: Owns driving enterprise-wide ROI and adoption programs. Increasingly accelerates customer autonomy with improved cadences and executive sponsorship through QBRs, strategic roadmaps, and enterprise-wide value opportunities. Enables cross-functional alignment and establishes repeatable frameworks for customers to independently track, realize, and expand on business value.\n Domain \u0026 Industry Leadership:  Serve as the internal and external technical subject matter expert for your customer industry domain to scale knowledge across the organization.\n AI Discovery \u0026 Solutioning: Understand your customers' AI strategies and specific challenges. As a Celonis product expert, find the best problem-solution fit and translate customer requirements into innovative solutions that deliver measurable impact.\n \n Requirements: \n \n 4+ years of experience in pre-sales, customer success, and/or consulting functions with a background in pre/post- sales consulting, strategy consulting, business process improvement, digital transformations, or customer value realization\n Strong Technical Skills across Microsoft or competitor equivalent (e.g., AWS) certification in relevant technologies (e.g. Azure, Data Engineering..etc). Knowledge of Data Connections, Data Objects, Data Validation and Data Analysis. Knowledge and use of LLM’s, across Microsoft or competitor equivalent (e.g. Claude, Copilot…etc). Understanding of basic prompting and data constructs within a prompt. \n Value driven selling through expertise in identifying and prioritising use cases, implementing improvement measures and becoming a change agent for the customer by establishing an operating model and training users for the customer to realize value and renew/expand their subscription with Celonis\n Project Management: You are able to plan and manage project scope, expectations and timelines. You will need to manage multiple projects across your aligned accounts that will be at different parts of the value journey. Also, you will leverage partners from the Celonis Ecosystem wherever possible.\n Strong presentation skills to both internal and external stakeholders, whether leading technical whiteboarding sessions or formal readouts and demos.\n Bachelor’s Degree required; Focus in computer science, engineering, mathematics, or related fields, or equivalent work experience preferred.\n \n   Nice to have (big plus): \n \n Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.\n Good knowledge of Python and common ML libraries (such as LangChain, pandas, sklearn, PyTorch) as well as data engineering tools and technologies.\n Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt","salary_min":137000,"salary_max":161000,"location":"New York, NY","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["agents","code-generation","llm","pytorch"],"apply_url":"https://job-boards.greenhouse.io/celonis/jobs/7742463003?gh_jid=7742463003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-22T18:00:22Z","expires_at":"2026-06-29T14:08:23.559759Z","created_at":"2026-05-27T14:08:37.038657Z","updated_at":"2026-05-30T14:08:23.678122Z","company_name":"Celonis","company_slug":"celonis","company_logo_url":"https://www.google.com/s2/favicons?domain=www.celonis.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f2e1438f-11be-4b9b-a71c-550e78f26436"},{"id":"31539a5e-cc10-4277-ac39-bd766925c679","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Staff Machine Learning Engineer, Programmatic Ads","slug":"staff-machine-learning-engineer-programmatic-ads-019343aa","description":"About Pinterest: \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .\n Pinterest is building a new Programmatic Ads ML team to bring in exchange-sourced ads demand and supply. We’re looking for a Staff ML engineer to develop core bidding and ranking systems that help us optimally buy and sell inventory across exchanges, driving strong ROI for advertisers and growing a critical revenue stream for Pinterest.\n  \n What you’ll do: \n \n Design and implement algorithms for real-time bidding, ad scoring/ranking, inventory selection, and yield optimization across multiple exchanges.\n Own end-to-end ML systems: problem framing, metrics, data/feature design, model training, evaluation, and online experimentation.\n Introduce and productionize new exchange and supply signals (e.g., quality, conversions, identity, fraud, content understanding) to unlock incremental advertiser value.\n Partner closely with Ads Ranking \u0026 Bidding, Measurement, and Programmatic Engineering to integrate new models and objectives into the ads stack.\n Use AI to accelerate analysis, experimentation, and iteration (e.g., exploring model variants, automating path from learnings to launch) while applying strong judgment and vision.\n \n  \n What we’re looking for \n \n Industry experience building and shipping large-scale production ML systems in ads, search, recommendations, or related domains.\n Deep experience with control/optimization algorithms for bidding, pacing, allocation, or similar marketplace problems.\n Strength in probabilistic modeling and measurement (e.g., quality/fraud signals, deep-learning engagement prediction) and making principled trade-offs between coverage, accuracy, and impact.\n Proven Staff-level technical leadership as an IC: driving technical direction and cross-team alignment without formal people management.\n Demonstrated ability to use AI to improve speed and quality of your workflow, with a strong track record of validating and stress-testing AI-assisted outputs.\n Degree in Computer Science, Statistics, or a related field.\n Experience with Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring.\n Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration.\n \n  \n Relocation Statement :\n \n This position is not eligible for relocation assistance. Visit our  PinFlex page to learn more about our working model.\n \n  \n In-Office Requirement Statement :.\n \n We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.\n This role will need to be in the office for in-person collaboration 3 times per quarter and therefore needs to be in a commutable distance from one of the following offices: San Francisco, Palo Alto, Seattle.\n \n #LI-SM4\n At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.\n Information regarding the culture at Pinterest and benefits available for this position can be found here . \n US based applicants only\n $222,716 — $389,753 USD \n Our Commitment to Inclusion: \n Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientati","salary_min":222716,"salary_max":389753,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["llm","fine-tuning","code-generation","machine-learning"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=7494765","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-19T21:22:51Z","expires_at":"2026-06-29T14:08:28.340035Z","created_at":"2026-05-27T14:08:42.016779Z","updated_at":"2026-05-30T14:08:28.454973Z","company_name":"Pinterest","company_slug":"pinterest","company_logo_url":"https://www.google.com/s2/favicons?domain=www.pinterest.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/31539a5e-cc10-4277-ac39-bd766925c679"},{"id":"8006684c-30cc-4625-b66e-db7474fce1dd","company_id":"66e863fb-9aaf-40df-996c-eb439e6f857e","title":"Software Engineer, APIs \u0026 Context Platform","slug":"software-engineer-apis-context-platform-ca8b3f32","description":"About Glean: \n  \n Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. \n  \n At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. \n  \n Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. \n  \n If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. \n About the Role: \n Glean is building the horizontal AI platform that powers how employees use AI at work – not just in Glean, but across tools like Copilot, Gemini, ChatGPT, IDEs, and more. We are seeking creative engineers to build this context platform and deliver rich, trustworthy experiences across all of those apps. This team owns the platform experience end‑to‑end: standards and tooling for REST APIs, SDKs and client libraries, agent SDKs and integrations, MCP servers, custom context such as code and memory, and the infrastructure and docs that make it easy to build on Glean. In a rapidly growing startup, this means working across multiple layers of the stack – backend services, developer tools, SDKs, and docs. \n You will: \n \n Own and evolve Glean's REST API standards: versioning strategy, backward-compatibility guarantees, deprecation policy, and OpenAPI specification tooling. \n Design and ship new API endpoints that expose Glean's platform primitives — search, knowledge graph, chat, agent and others  — as stable, well-documented developer surfaces. \n Build the API gateway layer: routing, authentication (OAuth2, API keys, OIDC), rate limiting, quota management, and per-tenant usage metering. \n Define reusable platform primitives on top of Glean's horizontal layers (connectors, security/governance, knowledge graph, memory, model orchestration) so they can be composed by internal teams and external partners. \n Work across backend services, developer tools, SDKs, and documentation in a fast-moving startup environment. \n Design, build, and evolve SDKs and client libraries that developers use to integrate with Glean from their own applications and agent frameworks. \n Instrument API usage to surface adoption metrics, error patterns, and latency SLOs \n Champion the external developer perspective internally — bring customer feedback, friction points, and feature requests into the roadmap process. \n \n About you: \n \n BA/BS in computer science or a related field, or equivalent practical experience. \n 5+ years of industry software engineering experience, with meaningful time spent building and shipping public-facing APIs or developer platforms in production. \n Deep fluency in REST API design principles: versioning, backward compatibility, pagination, error semantics, hypermedia, and OpenAPI/JSON Schema. \n Proficiency in at least one modern backend language (ideally Golang, or strong interest in learning it); experience with TypeScript, Python, and/or Java is a plus. \n Thrive in a customer‑focused, tight‑knit, cross‑functional environment – being a team player and willing to take on whatever is most impactful for the company is a must. \n A proactive and positive attitude to lead, learn, troubleshoot, and take ownership of both small tasks and large features. \n \n Location: \n \n This role is hybrid (4 days a week i","salary_min":210000,"salary_max":260000,"location":"Mountain View, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["code-generation","cloud","agents","api-design","llm","platform"],"apply_url":"https://job-boards.greenhouse.io/gleanwork/jobs/4696752005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-19T17:11:22Z","expires_at":"2026-06-29T14:03:15.987657Z","created_at":"2026-05-27T14:03:28.076552Z","updated_at":"2026-05-30T14:03:16.095756Z","company_name":"Glean","company_slug":"glean","company_logo_url":"https://www.google.com/s2/favicons?domain=glean.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8006684c-30cc-4625-b66e-db7474fce1dd"},{"id":"8cb71025-eb0b-4d8d-87cf-97b2cd416617","company_id":"7455e78c-482b-4f7b-9d62-11b78645818a","title":"Software Engineer II - Model Platform","slug":"software-engineer-ii-model-platform-ee0e16bc","description":"About the Role\n Abnormal AI is looking for a Software Backend Engineer II to join the Detection Team. The Detection Division is focused on building the world’s most advanced technology for identifying and stopping email and cloud-based attacks that were previously undetectable and help make the world a safer place. As a Software Engineer focused on building systems for Detection’s Model Platform, you will be responsible for making feature development at Abnormal a fast, responsive, stable, and confident experience for our ML and Data Science team.\n The ideal candidate would have the following qualities:\n \n A first principles approach to building scalable, customer-centric solutions\n A drive to solve meaningful \u0026 pragmatic problems for real-world people\n An ownership and impact oriented outlook on your efforts and growth\n An ability to iterate in real-time-solving novel problems, quickly and autonomously\n An ability to iterate in real-time - solving novel problems, quickly and autonomously\n \n What you will do \n \n Leverage the industry standard AI tools to architect, design, build, deploy and maintain Model Serving infrastructure that supports a world-class Detection Engine\n Own projects that scale our model serving and data processing services to handle 10x the traffic we serve today\n Own real-time, near real-time streaming pipelines, and online feature serving services\n Collaborate closely with MLE and Data Science teams by distilling feedback, correlating it to strategy, and executing\n \n Must Haves \n \n 4+ years of experience as a Software Engineer or in a similar role, with hands-on experience in building data-focused solutions.\n Proficiency leveraging AI tools to accelerate engineering outcomes, through the discovery, design, implementation and rollout of software systems \n Experience with maintaining large scale distributed systems on cloud platforms such as AWS, GCP, or Azure, including a strong grasp of best practices in cloud-based engineering.\n Familiarity with maintaining real-time and near real-time data pipelines or streaming services\n Experience working with distributed teams , proficient in asynchronous and written communication\n Excellent problem-solving skills and the ability to work independently in a fast-paced environment. You’re capable of breaking down complex challenges into manageable steps and iterating on solutions, balancing immediate needs with long-term scalability.\n You’re growth driven \u0026 looking to increase impact \u0026 responsibility over time\n Strong fundamentals in computer science, data structures, and performance optimization.\n BS degree in Computer Science, Applied Sciences, Information Systems or other related engineering field\n \n Nice to Have \n \n Familiarity with our stack (AWS, K8, Python/Django, Golang, Postgres)\n Experience / passion in building scalable, enterprise-grade applications.\n Experience with web security (eg. OWASP top 10)\n Familiarity with AI development tools such as Cursor, GitHub Copilot, or Claude.\n \n #LI-RT1\n Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location. In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package.\n Base salary range:\n $149,200 — $214,500 USD \n Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please  click here . If you would like more information on your EEO rights under the law, please  click here .","salary_min":149200,"salary_max":214500,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"mid","tags":["data-pipeline","mlops","distributed-systems","code-generation"],"apply_url":"https://abnormal.ai/careers/jobs/7734901003?gh_jid=7734901003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-19T12:48:55Z","expires_at":"2026-06-29T14:03:48.395552Z","created_at":"2026-05-19T14:04:09.840032Z","updated_at":"2026-05-30T14:03:48.512276Z","company_name":"Abnormal Security","company_slug":"abnormal-security","company_logo_url":"https://www.google.com/s2/favicons?domain=abnormalsecurity.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8cb71025-eb0b-4d8d-87cf-97b2cd416617"},{"id":"9f4195d7-f223-4644-bba5-da9c9e66f839","company_id":"a0000000-0000-0000-0000-000000000001","title":"Product Manager, Developer Productivity","slug":"product-manager-developer-productivity-48e76021","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 Product Manager focused on Developer Productivity, you'll partner with Infrastructure, Inference, Research, and Product Engineering to build the systems that determine how thousands of engineers and researchers at Anthropic develop, build, test, and ship code—the foundation on which every model, evaluation, and product feature depends:\n \n Partner with Developer Productivity engineering teams to own the end-to-end developer experience—from the source control and language ecosystems that underpin our monorepo, to the build and CI infrastructure that keeps thousands of daily builds running reliably across multiple cloud providers, to the acceleration tooling that deeply integrates Claude into every engineer's workflow.\n Your work directly impacts engineering velocity across the entire company: defining the abstractions for how code moves from idea to production, establishing the metrics that surface friction before it compounds, and making the trade-offs that keep a rapidly scaling engineering organization shipping with confidence.\n You'll drive the evolution of our developer platform through a fundamental shift in how software gets built—as AI agents move from autocomplete to autonomous collaborators, the definition of \"developer\" is changing, and our tooling, governance, and workflows must change with it. You'll be defining what developer productivity means when a meaningful share of code is written, tested, and reviewed by Claude itself.\n You will define and own the strategy and roadmap across build systems, CI/CD pipelines, developer environments, accelerator toolchain management (GPU, TPU, Trainium), and the AI-native acceleration layer that makes Anthropic the most productive place in the world to build frontier AI.\n \n Responsibilities: \n \n Deeply understand the needs of internal customers across Research, Inference, Infrastructure, and Product—from researchers iterating on training code who need fast, reproducible builds to inference engineers managing compute-intensive toolchains with strict compatibility constraints.\n Define and iterate on the developer experience model: the workflows, tooling primitives, and feedback loops that govern how engineers and AI agents collaborate on code—including how we measure productivity when the unit of work is no longer a human typing.\n Partner with engineering leads to design build, CI, and test infrastructure that scales non-linearly with engineering headcount—ensuring that as Claude takes on more of the inner loop, the outer loop (review, validation, deployment) doesn't become the new bottleneck.\n Drive product strategy and roadmap for developer acceleration, including AI-assisted code review, agent-driven test generation, automated dependency management, and the governance frameworks that let teams safely delegate work to autonomous systems.\n Own the trade-off framework between velocity, reliability, security, and cost—making transparent prioritization decisions about where to invest in human workflows versus agent workflows, and communicating them clearly to senior leadership.\n Establish and champion the productivity metrics that matter in an AI-native engineering org—moving beyond commits and cycle time to measures that capture human-agent collaboration effectiveness, toil eliminated, and time-to-confident-ship.\n Build conviction about where developer tooling is headed on a 2–3 year horizon, and translate that into a roadmap that keeps Anthropic ahead of—not reacting to—the exponential curve of AI-assisted development.\n \n You may be a good fit if you have:\n \n 7+ years of product management experience, with deep exposure to developer tooling, build systems, CI/CD, or platform infrastructure\n Experience taking technical platform products from infancy to scale—you've built something from the ground up and grown it to serve demanding internal or external engineering customers\n Track record of building platform products that balance the needs of multiple engineering personas—you're comfortable making prioritization trade-offs between velocity, reliability, and security, and communicating them clearly\n Ability to internalize complex technical systems (build systems, monorepos, CI pipelines, accelerator toolchains) and translate that understanding into a comprehensive product vision\n Fluent across functions—you're equally credible discussing build graph optimization with engineers, developer velocity economics with leadership, and AI-agent governance with security teams\n A strong thesis on how AI will reshape software development—you've thought deeply about what changes when agent","salary_min":385000,"salary_max":595000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["agents","cloud","alignment","gpu","code-generation"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5220143008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-19T10:34:22Z","expires_at":"2026-06-29T14:00:19.557033Z","created_at":"2026-05-19T14:00:21.471137Z","updated_at":"2026-05-30T14:00:19.669103Z","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/9f4195d7-f223-4644-bba5-da9c9e66f839"},{"id":"870a50fb-c75f-4fb9-9b7e-ffc6b8d7ce5d","company_id":"d66267b6-f404-410f-9b8e-fe8bbcfcaf1b","title":"Senior Software Engineer (Typescript / FrontEnd) - AI/ML","slug":"senior-software-engineer-typescript-frontend-aiml-35fbefe6","description":"About ClickHouse\n Recognized on the 2025 Forbes Cloud 100 list, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 3,000 customers and ARR that has grown over 250 percent year over year, ClickHouse leads the market in real-time analytics, data warehousing, observability, and AI workloads.\n The company’s sustained, accelerating momentum was recently validated by a $400M Series D financing round. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla.\n We’re on a mission to transform how companies use data. Come be a part of our journey!\n The AI/ML Engineering team builds and operates ClickHouse's AI and machine learning products end-to-end. This includes the Agentic Data Stack, AI Functions, chDB, the in-Console copilot, and the AI/ML partnerships that distribute them — together with the shared components and expertise that let every other ClickHouse team ship AI in the surfaces they own. Our team is looking for highly skilled and experienced software engineers to join us, who will be responsible for designing, building, and operating the products that make ClickHouse the platform of choice for agents and data scientists. \n What will you do? \n \n Feature Development: Design and implement AI-powered features across the full stack, from backend inference services to intuitive frontend interfaces within the ClickHouse Cloud platform.\n API Architecture: Create robust, scalable APIs that connect ClickHouse's database capabilities with modern AI/ML inference systems and external/internal AI services.\n UI/UX Implementation: Build responsive, intuitive user interfaces that make complex AI functionalities accessible and valuable to users of all technical backgrounds.\n Ecosystem Integrations: Implement and maintain integrations with the broader AI/ML ecosystem and standards, ensuring that ClickHouse as a technology works seamlessly with popular frameworks and tools.\n Technical Integration: Integrate models into production systems with proper monitoring, versioning, observability, and evaluation.\n \n What you bring along: \n \n 5+ years of software engineering experience in production environments \n Exposure to working directly with AI/ML technologies\n Strong frontend skills with TypeScript/JavaScript and React\n Backend development experience in TypeScript or Python, with a focus on API design and service architecture\n You have a high level of ownership and can drive features from concept to production with minimal supervision\n You thrive in collaborative environments and can effectively communicate technical concepts to diverse stakeholders\n \n Nice to have \n \n Experience building data-oriented interfaces and visualizations\n Experience integrating and deploying AI/ML models in production systems, including working with inference APIs and vector databases\n Familiarity with cloud technologies such as AWS, Azure, or GCP, particularly services related to AI/ML deployment\n Understanding of database systems and data processing pipelines, with ClickHouse experience being a significant plus\n \n #LI-remote\n The typical starting salary for this role in the US is\n $141,000 — $195,000 USD \n The typical starting salary for this role in US Premium Markets is\n $158,000 — $232,000 USD \n Compensation \n For roles based in the  United States , t he typical starting salary range for this position is listed above. In certain locations, such as the San Francisco Bay Area and the New York City Metro Area, a premium market range may apply, as listed.\n These salary ranges reflect what we reasonably and in good faith believe to be the minimum and maximum pay for this role at the time of posting. The actual compensation may be higher or lower than the amounts listed, and the ranges may be subject to future adjustments.\n An individual’s placement within the range will depend on various factors, including (but not limited to) education, qualifications, certifications, experience, skills, location, performance, and the needs of the business or organization.\n If you have any questions or comments about compensation as a candidate, please get in touch with us at  paytransparency@clickhouse.com . \n Perks \n \n Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 20 countries. \n Healthcare - Employer contributions towards your healthcare. \n Equity in the company - Every new team member who joins our company receives stock options. \n Time off - Flexible time off in the US, generous entitlement in other countries. \n A $500 Home office setup if you’re a remote employee. \n Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsit","salary_min":158000,"salary_max":232000,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["healthcare","code-generation","agents","api-design","embeddings","frontend","typescript","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/clickhouse/jobs/5996876004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-18T12:35:56Z","expires_at":"2026-06-29T14:13:50.992332Z","created_at":"2026-05-27T14:14:25.615889Z","updated_at":"2026-05-30T14:13:51.113512Z","company_name":"ClickHouse","company_slug":"clickhouse","company_logo_url":"https://www.google.com/s2/favicons?domain=clickhouse.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/870a50fb-c75f-4fb9-9b7e-ffc6b8d7ce5d"},{"id":"bef8e55e-fe6d-4a67-b298-d6a8b83d6b26","company_id":"a0000000-0000-0000-0000-000000000003","title":"Senior Staff Frontier Agents Engineer","slug":"senior-staff-forward-deployed-ai-engineer-enterprise-c23669bc","description":"About Scale AI \n Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.\n Role Overview \n As a Senior Staff Forward Deployed AI Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments.\n This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows.\n Key Responsibilities \n Customer Integration \u0026 Deployment \n \n Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements\n Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)\n Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows\n Deploy and configure AI models and agents within customer security and compliance boundaries\n \n AI Agent Development \n \n Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation\n Architect multi-agent systems that orchestrate between different models, tools, and data sources\n Implement evaluation frameworks to measure agent performance and iterate toward business objectives\n Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement\n \n Prompt Engineering \u0026 Optimization \n \n Create sophisticated prompt engineering strategies optimized for customer-specific domains and data\n Build and maintain prompt libraries, templates, and best practices for customer use cases\n Conduct systematic prompt experimentation and A/B testing to improve model outputs\n Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate\n \n Technical Leadership \u0026 Collaboration \n \n Serve as the primary technical point of contact for strategic enterprise accounts\n Collaborate with customer data scientists, ML engineers, and software developers to ensure smooth integration\n Provide technical training and knowledge transfer to customer teams\n Work closely with Scale's product and engineering teams to translate customer needs into product improvements\n Document technical architectures, integration patterns, and best practices\n \n Problem Solving \u0026 Innovation \n \n Debug complex technical issues across the entire stack, from data pipelines to model outputs\n Rapidly prototype solutions to unblock customers and prove out new use cases\n Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems\n Identify opportunities for productization based on common customer patterns\n \n Required Qualifications \n \n 12+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design\n Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)\n Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure\n Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions\n Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences\n \n Preferred Qualifications \n Agent Development Wiz \n \n Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures\n Experience building and deploying AI agents or autonomous systems in production\n Knowledge of vector databases and semantic search systems\n Contributions to open-source AI/ML projects\n \n Infrastructure Guru \n \n Experience with containerization (Docker, Kubernetes) and CI/CD pipelines\n Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools\n Previous work in a devops, platform, or infra role\n Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)\n \n Customer Product Whisperer \n \n Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role\n Domain expertise in verticals like finance, healthcare, government, or manufacturing\n Experience with technical enablement or teaching programs\n \n Sample Projects \n The following are some examples of the types of projects we’ve worked on with customers. All of these projects leverage customer da","salary_min":288000,"salary_max":360000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["code-generation","healthcare","rag","search","llm","generative-ai","embeddings","agents"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4694869005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-15T23:55:32Z","expires_at":"2026-06-29T14:01:13.721439Z","created_at":"2026-05-16T14:01:23.031903Z","updated_at":"2026-05-30T14:01:13.834308Z","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/bef8e55e-fe6d-4a67-b298-d6a8b83d6b26"},{"id":"ea24f46c-dc37-4f7b-a5f1-63431c79c43e","company_id":"a0000000-0000-0000-0000-000000000003","title":"Staff Frontier Agents Engineer ","slug":"staff-forward-deployed-ai-engineer-enterprise-c0df4021","description":"About Scale AI \n Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.\n Role Overview \n As a Staff Forward Deployed AI Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments.\n This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows.\n Key Responsibilities \n Customer Integration \u0026 Deployment \n \n Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements\n Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)\n Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows\n Deploy and configure AI models and agents within customer security and compliance boundaries\n \n AI Agent Development \n \n Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation\n Architect multi-agent systems that orchestrate between different models, tools, and data sources\n Implement evaluation frameworks to measure agent performance and iterate toward business objectives\n Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement\n \n Prompt Engineering \u0026 Optimization \n \n Create sophisticated prompt engineering strategies optimized for customer-specific domains and data\n Build and maintain prompt libraries, templates, and best practices for customer use cases\n Conduct systematic prompt experimentation and A/B testing to improve model outputs\n Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate\n \n Technical Leadership \u0026 Collaboration \n \n Serve as the primary technical point of contact for strategic enterprise accounts\n Collaborate with customer data scientists, ML engineers, and software developers to ensure smooth integration\n Provide technical training and knowledge transfer to customer teams\n Work closely with Scale's product and engineering teams to translate customer needs into product improvements\n Document technical architectures, integration patterns, and best practices\n \n Problem Solving \u0026 Innovation \n \n Debug complex technical issues across the entire stack, from data pipelines to model outputs\n Rapidly prototype solutions to unblock customers and prove out new use cases\n Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems\n Identify opportunities for productization based on common customer patterns\n \n Required Qualifications \n \n 8+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design\n Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)\n Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure\n Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions\n Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences\n \n Preferred Qualifications \n Agent Development Wiz \n \n Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures\n Experience building and deploying AI agents or autonomous systems in production\n Knowledge of vector databases and semantic search systems\n Contributions to open-source AI/ML projects\n \n Infrastructure Guru \n \n Experience with containerization (Docker, Kubernetes) and CI/CD pipelines\n Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools\n Previous work in a devops, platform, or infra role\n Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)\n \n Customer Product Whisperer \n \n Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role\n Domain expertise in verticals like finance, healthcare, government, or manufacturing\n Experience with technical enablement or teaching programs\n \n Sample Projects \n The following are some examples of the types of projects we’ve worked on with customers. All of these projects leverage customer data, inte","salary_min":252000,"salary_max":315000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["embeddings","llm","healthcare","search","data-pipeline","fine-tuning","rag","code-generation"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4694865005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-15T23:54:36Z","expires_at":"2026-06-29T14:01:14.746596Z","created_at":"2026-05-16T14:01:24.232193Z","updated_at":"2026-05-30T14:01:14.857364Z","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/ea24f46c-dc37-4f7b-a5f1-63431c79c43e"}],"page":1,"per_page":20,"total":304,"total_pages":16}