{"has_next":true,"jobs":[{"id":"8b3dbb78-3093-481e-9b0c-09e3ed1deb6e","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Principal Software Engineer, Data","slug":"principal-software-engineer-data-0cdb1bea","description":"Your Impact at LILA \n Join us in shaping the future of science! We are seeking Principal Software Engineers with backend experience to join our Data Platform Team (Data), where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!\n About The Team \n The Data Platform Team (Data) builds and support the data systems that underpins Lila's AI Science Factory™. Every experiment run in our labs, every measurement from an instrument, and every signal from our operational systems flows through the platform they build. Their work spans real-time ingestion, large-scale analytical storage, workflow orchestration, and the self-service tools scientists, engineers, and ML teams use to go from raw measurements to discoveries. They build the data backbone of Scientific Superintelligence™, so the science moves faster and each experiment makes the next one smarter.\n What You'll Be Building \n \n Design \u0026 Build APIs: Design and build high-performance, secure, and well-documented APIs that integrate with AI-driven applications.\n Database Architecture \u0026 Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.\n Performance \u0026 Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.\n Cloud \u0026 Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.\n Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.\n \n What You'll Need To Succeed \n \n Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.\n 8-15 years of engineering experience building and deploying large-scale systems in production. You must be strong in scalable backend system design.\n Full Stack Development : Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)\n Experience with ORMs: Experience with and web services for CRUD services (SQL Alchemy, SQLModel, FastAPI, Django).\n Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).\n Familiarity with Python for Science : Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).\n Hands on experience using AI coding assistants to drive productivity is required.\n Communication \u0026 Collaboration : Acute listening and writing skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving : Proven ability to design complex backend solutions, balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Cloud \u0026 DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).\n Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.\n Experience with laboratory devices, robotics, or hardware\n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.\n Expected Base Salary Range\n $204,000 — $348,000 USD \n About LILA \n Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.\n LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials","salary_min":204000,"salary_max":348000,"location":"Boston, MA","workplace":"onsite","job_type":"full-time","experience_level":"principal","tags":["cloud","pytorch","embeddings","robotics","data-pipeline"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4250071009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T19:39:54Z","expires_at":"2026-06-29T14:17:40.451966Z","created_at":"2026-05-30T14:17:40.562155Z","updated_at":"2026-05-30T14:17:40.562155Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8b3dbb78-3093-481e-9b0c-09e3ed1deb6e"},{"id":"c4efb161-7f94-4ca1-8b5e-49dba720ed4a","company_id":"01048ffd-9864-41e0-a719-14b849fbcbcd","title":"Mission Integration Engineer, AI (Starshield)","slug":"mission-integration-engineer-ai-starshield-f7ba9f64","description":"SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today SpaceX is actively developing the technologies to make this possible, with the ultimate goal of enabling human life on Mars.\n MISSION INTEGRATION ENGINEER, AI (STARSHIELD) \n Special Programs leverages technology and launch capability to support national security efforts. Starshield, within Special Programs, is designed for government use, with an initial focus on earth observation, communications, and hosted payloads.\n The data applications team is building highly reliable mission-critical AI solutions supporting Starshield use-cases. You will drive the development and enhancement of core applications while collaborating cross-functionally to deliver end-to-end products. Aerospace experience is not required to be successful here—we want our engineers to bring fresh ideas from all areas. We look for engineers who love solving problems and seek to make an impact on an inspiring mission. As we expand this team, we’re looking for versatile, motivated, and collaborative engineers.\n Our team is responsible for identifying pain points, scoping product specifications, and designing and building LLM-powered software for government or enterprise use cases. This role will enhance model performance through system prompt tuning or fine-tuning, with an eye toward secure and scalable deployment.\n RESPONSIBILITIES: \n \n Develop full-stack solutions to manage scalable AI content interaction systems with user applications\n Develop prototypes to prove key design concepts and quantify technical constraints\n Apply creativity to build an immersive earth observation experience for users whether they are in offices or in the field\n See your software through from start-to-finish: from figuring out the core needs to prototyping, developing, and testing; to production rollout and beyond\n \n BASIC QUALIFICATIONS: \n \n Bachelor’s degree in computer science, data science, physics, mathematics, or engineering discipline\n Experience with Javascript libraries such as React, Angular, and/or Redux\n Professional experience developing Python applications\n \n PREFERRED SKILLS AND EXPERIENCE: \n \n Professional experience developing web services and distributed applications across cloud and on-premise networks\n Professional experience developing within Linux server environments, SSH, scripting, and configuration\n Experience with Kubernetes or similar container orchestration frameworks\n Experience with Model Context Protocol or large model content interaction systems\n Experience with developing RAG pipelines, tool callers, and AI orchestration systems\n Experience with Vector databases or implementing highly performant databases\n Experience with image data processing and machine learning\n Experience with graphics-intensive web application development\n \n ADDITIONAL REQUIREMENTS: \n \n Must be willing to work extended hours and weekends as needed\n Active Top Secret, Top Secret SCI, or DOE Level Q clearance\n An active clearance may provide the opportunity for you to work on sensitive SpaceX missions; if so, you will be subject to pre-employment drug and random drug and alcohol testing\n \n  \n COMPENSATION AND BENEFITS: \n Pay Range:   Mission Integration Engineer/Level I: $100,000.00 - $115,000.00/per year. Mission Integration Engineer/Level II: $110,000.00 - $135,000.00/per year.     \n Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, and experience. Those with an active clearance will receive a 10% differential, up to an additional $20,000 annually, once officially briefed into a classified program.\n Base salary is just one part of your total rewards package at SpaceX. You may also be eligible for long-term incentives, in the form of company stock, stock options, or long-term cash awards, as well as potential discretionary bonuses and the ability to purchase additional stock at a discount through an Employee Stock Purchase Plan. You will also receive access to comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short \u0026 long-term disability insurance, life insurance, paid parental leave, and various other discounts and perks. You may also accrue 3 weeks of paid vacation \u0026 will be eligible for 10 or more paid holidays per year. Employees accrue paid sick leave pursuant to Company policy which satisfies or exceeds the accrual, carryover, and use requirements of the law.\n ITAR REQUIREMENTS: \n \n To conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder), (iii) Refugee under 8 U.S.C. § 1157, or (iv) Asylee under 8 U.S.C. § 1158, or be eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the IT","salary_min":110000,"salary_max":135000,"location":"Hawthorne, CA","workplace":"onsite","job_type":"full-time","experience_level":"mid","tags":["embeddings","fine-tuning","rag","llm"],"apply_url":"https://boards.greenhouse.io/spacex/jobs/8569184002?gh_jid=8569184002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T21:57:12Z","expires_at":"2026-06-29T14:16:59.105031Z","created_at":"2026-05-29T15:07:10.614713Z","updated_at":"2026-05-30T14:16:59.217294Z","company_name":"SpaceX","company_slug":"spacex","company_logo_url":"https://www.google.com/s2/favicons?domain=spacex.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/c4efb161-7f94-4ca1-8b5e-49dba720ed4a"},{"id":"0ed6f2c3-8d05-4541-a58a-3bc3eb48b078","company_id":"1a3abe34-d1c1-45b9-9259-3e2e007a961c","title":"Staff Research Scientist","slug":"staff-research-scientist-6193df9d","description":"About Voyage AI Team at MongoDB\n Voyage AI team in MongoDB is building a best-in-class, general-purpose, domain-specific, and fine-tuned embedding models and rerankers to enable accurate, efficient unstructured data search and retrieval for RAG, recommendation, semantic search, and more. It is backed by a strong team of AI researchers from Stanford, MIT, Berkeley, Princeton, and CMU, who have conducted over five years of cutting-edge research on training embedding models. Voyage AI was acquired by MongoDB recently, and is now integrating the SOTA embedding models with MongoDB's data platform to create powerful end-to-end solutions.\n Position Overview\n We are seeking a Staff Research Scientist to join our team and contribute to the development of next-generation AI models. This position offers a unique opportunity to work on challenging problems at the intersection of machine learning research and practical deployment of large neural networks.\n This role can be based out of our Palo Alto office, or remotely in the United States.\n Responsibilities\n \n Conduct cutting-edge research in artificial intelligence, from frontier LLMs to embedding models and rerankers\n Innovate in next-generation information retrieval and LLM agent paradigm\n Collaborate closely with other research scientists and research engineers as well as peers across the organization\n \n Qualifications\n \n PhD degree in Computer Science or related field\n A track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications in top venues\n Strong background in machine learning, deep learning, and natural language processing\n Experience building complex neural networks for language and visual understanding\n Capable of conducting rigorous empirical studies to validate theoretical results\n Excellent leadership, problem-solving, and communication skills\n \n What We Offer\n \n Opportunity to work on real-world problems at the cutting edge of AI research\n Opportunity to utilize research vision to innovate the entire company and make real-world impact\n Exposure to the full lifecycle of AI model development, from research to production\n Our compensation (base + equity) for this position is competitive with frontier AI labs\n \n About MongoDB \n MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.\n With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.\n Our compass at MongoDB is our  Leadership Commitment,  guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB.\n To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone.  From employee affinity groups, to fertility assistance and a generous parental leave policy , we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys.  Learn more about what it’s like to work at MongoDB , and help us make an impact on the world!\n MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.\n MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.\n Req ID: 2273454547\n MongoDB’s base salary range for this role is posted below. Compensation at the time of offer is unique to each candidate and based on a variety of factors such as skill set, experience, qualifications, and work location. Salary is one part of MongoDB’s total compensation and benefits package. Other benefits for eligible employees may include: equity, participation in the employee stock purchase program, flexible paid time off, 20 weeks fully-paid gender-neutral parental leave, fertility and adoption assistance, 401(k) plan, mental health counseling, access to ","salary_min":151000,"salary_max":297000,"location":"Palo Alto, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["nlp","computer-vision","search","llm","embeddings","deep-learning","research"],"apply_url":"https://www.mongodb.com/careers/job/?gh_jid=7956670","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T17:21:23Z","expires_at":"2026-06-29T14:08:48.853182Z","created_at":"2026-05-29T14:32:41.960202Z","updated_at":"2026-05-30T14:08:48.964003Z","company_name":"MongoDB","company_slug":"mongodb","company_logo_url":"https://www.google.com/s2/favicons?domain=www.mongodb.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0ed6f2c3-8d05-4541-a58a-3bc3eb48b078"},{"id":"8f9c6077-75d0-4b5b-b703-965d816fb18b","company_id":"cf6855a4-6591-475f-be10-f3f36cf31758","title":"Senior Product Manager, AI Agent Orchestration","slug":"senior-product-manager-ai-agent-orchestration-11c09d00","description":"WHAT IS BOX?  \n Box (NYSE:BOX) is the leader in Intelligent Content Management. Our platform enables organizations to fuel collaboration, manage the entire content lifecycle, secure critical content, and transform business workflows with enterprise AI. We help companies thrive in the new AI-first era of business. Founded in 2005, Box simplifies work for leading global organizations, including JLL, Morgan Stanley, and Nationwide. Box is headquartered in Redwood City, CA, with offices across the United States, Europe, and Asia.\n By joining Box, you will have the unique opportunity to continue driving our platform forward. Content powers how we work. It’s the billions of files and information flowing across teams, departments, and key business processes every single day: contracts, invoices, employee records, financials, product specs, marketing assets, and more. Our mission is to bring intelligence to the world of content management and empower our customers to completely transform workflows across their organizations. With the combination of AI and enterprise content, the opportunity has never been greater to transform how the world works together and at Box you will be on the front lines of this massive shift.\n WHY BOX NEEDS YOU  \n Box AI is transforming the way businesses manage and leverage content by incorporating cutting-edge artificial intelligence and machine learning capabilities into the Box Content Cloud. As a Senior Product Manager for Box AI Agents , you will play a key role in building the next frontier of intelligent content management, leading AI-driven solutions that revolutionize how enterprises interact with their content.\n In this role, you will be at the helm of driving Box’s AI platform strategy, execution, and iteration, shaping the future of enterprise AI solutions . You’ll define and execute product roadmaps that leverage AI technologies, such as large language models (LLMs) and retrieval-augmented generation (RAG), to unlock insights, automate workflows, and improve collaboration across global enterprises. Your work will directly impact how businesses across the world manage and extract value from their content at scale.\n If you're passionate about defining and leading AI product strategies, bringing AI solutions to market, and driving real-world business impact, this is your chance to lead a high-impact role in the next chapter of Box’s AI growth.\n WHAT YOU'LL DO \n \n Lead the strategy and long-term architecture for Box's core AI orchestration platform — the foundational layer that powers how AI agents reason, plan, and act across the entire Box product surface.\n Define and own a technically complex, mission-critical product area at the intersection of AI infrastructure and enterprise-grade content workflows, balancing the needs of internal platform teams, external developers, and enterprise customers.\n Drive the next generation of agent architecture, anticipating how advances in AI reasoning, multi-step planning, and compute paradigms will reshape what's possible — and translating that vision into a concrete, sequenced roadmap.\n Serve as the connective tissue across every team building on the AI platform — establishing shared primitives, coordinating dependencies, and ensuring that foundational architectural decisions scale gracefully as adoption grows.\n Lead end-to-end product development for the orchestration layer: from identifying capability gaps and architectural constraints to shipping production-grade solutions and iterating based on real-world usage signals.\n Collaborate deeply with engineering and applied AI teams to design and evolve the systems that govern how tools are invoked, how context is managed, and how agents coordinate across complex, multi-turn workflows.\n Establish a rigorous, metrics-driven approach to platform health and capability maturity — defining the right signals to measure reliability, latency, and quality at scale across diverse enterprise use cases.\n Partner cross-functionally with teams across features, infrastructure, and go-to-market to ensure the platform's capabilities are well-understood, well-documented, and effectively leveraged by every team building on top of it.\n Stay at the leading edge of the AI agent landscape — continuously evaluating emerging patterns in orchestration, tool use, and agentic compute — and bringing that perspective to bear on Box's platform strategy.\n \n WHAT YOU'LL DO  \n \n Lead the strategy and long-term architecture for Box's core AI orchestration platform — the foundational layer that powers how AI agents reason, plan, and act across the entire Box product surface.\n Define and own a technically complex, mission-critical product area at the intersection of AI infrastructure and enterprise-grade content workflows, balancing the needs of internal platform teams, external developers, and enterprise customers.\n Drive the next generation of agent architecture, anticipating how advances in AI reasoni","salary_min":192500,"salary_max":240500,"location":"Redwood City, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["rag","embeddings","cloud","fine-tuning","llm","agents"],"apply_url":"https://job-boards.greenhouse.io/boxinc/jobs/7959067","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-27T16:34:48Z","expires_at":"2026-06-29T14:19:20.680259Z","created_at":"2026-05-28T14:21:03.444277Z","updated_at":"2026-05-30T14:19:20.791946Z","company_name":"Box","company_slug":"box","company_logo_url":"https://www.google.com/s2/favicons?domain=box.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8f9c6077-75d0-4b5b-b703-965d816fb18b"},{"id":"84366e11-6b70-4a34-a8c9-d03cd29bd00e","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Senior Applied Research Engineer","slug":"senior-applied-research-engineer-a868acf4","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata is seeking a Senior Applied Research Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research.\n\nThis is a research-focused role emphasizing experimentation and rigor over production engineering. You'll own the science behind how Drata's AI products retrieve, reason, and respond — and you'll work closely with AI and Software Engineers to turn validated approaches into production-ready systems.\n\nDrata's compliance platform is document-heavy: VRM Agent, AIQA, Trust Agent, policy-to-control mappers, and more all depend on high-quality information retrieval and reasoning.\n\nWhat you'll do:\n\n - Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, semantic routing\n\n - Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements ↔ evidence)\n\n - Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and structured prediction\n\n - Build and maintain evaluation frameworks: golden datasets, automated quality metrics, regression detection\n\n - Implement and tune ranking/reranking systems: cross-encoders, LLM-based rerankers, learning-to-rank, custom scoring functions\n\n - Run experiments to validate hypotheses and quantify improvements before production rollout\n\n - Debug failure modes and build error taxonomies across retrieval, reasoning, and generation\n\n - Collaborate with AI and Software Engineers to hand off validated approaches for productionization\n\n - Stay current on applied research in RAG, agents, LLM evaluation, and relevance modeling; bring innovations into the product\n\nWhat you'll bring:\n\n - 5+ years of experience in applied research, data science, or ML with a focus on NLP, information retrieval, or knowledge systems\n\n - 2+ years of hands-on experience building or contributing to production AI/ML systems\n\n - Strong foundation in information retrieval: dense and sparse retrieval, embedding models, search relevance\n\n - Experience with RAG systems: chunking strategies, vector databases, retrieval optimization\n\n - Proficiency in evaluation methodology: metrics design, golden dataset creation, A/B testing, statistical significance\n\n - Strong Python skills and comfort with notebook-driven research wo","salary_min":166900,"salary_max":225900,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["nlp","generative-ai","rag","embeddings","search","llm","agents","healthcare"],"apply_url":"https://jobs.ashbyhq.com/drata/fab401cd-087e-4b69-8a62-f0dbae4906c9/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T22:59:45.262Z","expires_at":"2026-06-29T14:13:57.168877Z","created_at":"2026-05-27T14:14:33.203504Z","updated_at":"2026-05-30T14:13:57.34909Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/84366e11-6b70-4a34-a8c9-d03cd29bd00e"},{"id":"4b838594-7738-4715-8dfb-17cd9c747ea8","company_id":"3029e985-56bf-4ac2-9ae1-df4cdd53b12f","title":"Principal GenAI Data Engineer ","slug":"principal-genai-data-engineer-9a655ea2","description":"About Zscaler \n Zscaler accelerates digital transformation to ensure our customers can be more agile, efficient, resilient, and secure. As an AI-forward enterprise , we are constantly pushing the envelope, leveraging the world’s largest security data lake to power our cloud-native Zero Trust Exchange platform. This innovation protects our customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location.\n Here, impact in your role matters more than title and trust is built on results. We say, impact over activity. We seek innovators who actively use AI to amplify their impact and who thrive in an environment where we leverage intelligent systems to stay ahead of evolving threats. We believe in transparency and value constructive, honest debate —we’re focused on getting to the best ideas, faster. We build high-performing teams that can make an impact quickly and with high quality. To do this, we are building a culture of execution centered on customer obsession , collaboration, ownership, and accountability.\n We value high-impact, high-accountability with a sense of urgency where you’re enabled to do your best work and embrace your potential. If you’re driven by purpose, thrive on solving complex challenges, and want to be part of the team that’s helping to secure the AI age, we invite you to bring your talents to Zscaler and help shape the future of cybersecurity.\n Role \n We are looking for a Principal GenAI Data Engineer to join our IT Data Strategy team. This role is fully remote within the US, reporting to the Senior Manager, Enterprise AI Data Platform. We are seeking an experienced technical leader to drive the design and implementation of enterprise-grade Generative AI data ingestion, knowledge preparation, and platform architectures that enable scalable, production-ready GenAI applications. This role focuses on architecting robust pipelines and platforms for ingesting, processing, governing, and serving structured and unstructured enterprise data for AI/LLM workloads. The ideal candidate combines deep expertise in enterprise data architecture, unstructured data pipelines, GenAI platform engineering, and strong software engineering skills in Python.\n What you’ll do (Role Expectations) \n \n Architect enterprise-scale GenAI data platforms for ingestion, transformation, enrichment, and serving of structured and unstructured data\n Design scalable pipelines for enterprise knowledge ingestion from diverse data sources including documents, SaaS platforms, knowledge bases, collaboration tools, and databases\n Define architecture for metadata extraction, chunking, enrichment, embeddings generation, and knowledge preparation workflows\n Design AI-ready data models and storage strategies for vector, graph, and hybrid knowledge systems\n Architect scalable unstructured data processing pipelines for text, images, PDFs, tables, and multimodal content\n \n Who You Are (Success Profile) \n \n You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. You adapt to what’s needed, navigating seamlessly between high-level strategy and hands-on execution.\n You are a problem-solver. You seek out challenges because you are energized by finding solutions, knowing that solving the hard problems delivers the biggest impact.\n You lead with integrity. You do the right thing, even when it’s hard. You hold yourself and others to a high standard of accountability and build trust by matching your words with consistent, transparent action.\n You think at scale. You connect your day-to-day work to the larger company mission and think globally. You build solutions, processes, and teams that are not just effective today but are built to last and support a high-growth, global organization.\n You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.\n \n What We’re Looking for (Minimum Qualifications) \n \n Expert-level Python programming and software engineering capabilities\n Experience building distributed/scalable data pipelines for AI workloads\n Strong understanding of unstructured data extraction and processing pipelines\n Experience with vector databases, graph databases, and metadata/knowledge storage systems\n Hands-on experience with clustering, entity recognition algorithms, and modern retrieval strategies (including RAG, search, and agentic AI workflows)\n \n What Will Make You Stand Out (Preferred Qualifications) \n \n Deep understanding of AI-ready data platform design principles and the ability to bridge platform/data engineering with GenAI/LLM application requirements\n Experience with LLMOps / GenAIOps frameworks such as LangSmith, Evaluation Framework like Arize","salary_min":182000,"salary_max":260000,"location":"Remote (US)","workplace":"hybrid","job_type":"full-time","experience_level":"principal","tags":["security","embeddings","data-pipeline","agents","generative-ai","llm","data-engineering"],"apply_url":"https://job-boards.greenhouse.io/zscaler/jobs/5142526007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T18:53:33Z","expires_at":"2026-06-29T14:09:18.592777Z","created_at":"2026-05-27T14:09:33.406845Z","updated_at":"2026-05-30T14:09:18.706338Z","company_name":"Zscaler","company_slug":"zscaler","company_logo_url":"https://www.google.com/s2/favicons?domain=zscaler.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4b838594-7738-4715-8dfb-17cd9c747ea8"},{"id":"77cc20d9-b485-408a-9a85-753c8c333d3c","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Senior Software Engineer, App","slug":"senior-software-engineer-app-e60d648a","description":"Your Impact at LILA Scientists shouldn't have to context-switch between a dozen tools to go from hypothesis to result. We're building the platform that makes this a reality — and we need engineers who want to solve problems no one has solved before.\n We're hiring Sr Principal / Principal Software Engineers to design the agents, interfaces, and platform integrations that let researchers seamlessly collaborate with AI.\n About The Team \n The Application Team sits at the center of LILA — the integration point where Machine Learning, Life Sciences, Physical Sciences, and Software become one AI-native experience that carries a scientist from hypothesis to experiment to breakthrough results.\n \n AI isn't a feature here — it's the architecture. Agent frameworks, tools, and LLM orchestration are core primitives, not bolt-ons.\n The problems are genuinely hard. Connecting AI to automated lab workflows, ML pipelines, and multi-domain knowledge graphs means inventing patterns, not copying them.\n You'll learn domains you never expected. Working shoulder-to-shoulder with lab scientists and ML engineers means your technical surface area grows fast.\n You'll ship things that matter. The tools you build accelerate research timelines from months to days.\n \n If you want to build at the intersection of AI and science, move fast without breaking trust, and grow into the kind of engineer who can architect systems that don't exist yet — we want to talk.\n \n What You'll Be Building \n \n Design \u0026 Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.\n Database Architecture \u0026 Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.\n Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.\n Performance \u0026 Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.\n Cloud \u0026 Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.\n Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.\n \n What You'll Need To Succeed \n \n Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.\n 5-8+ years of engineering experience building and deploying large-scale systems in production. You must be strong in backend.\n Full Stack Development : Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)\n Hands on experience using AI coding assistants to drive productivity is required.\n Communication \u0026 Collaboration : Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving : Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Applied AI Engineering: Experience building with AI agents, graph-based workflows, tool-use protocols (MCP), RAG pipelines, or LLM orchestration frameworks.\n Cloud \u0026 DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).\n Experience with ORMs: Experience with and web services for CRUD services (SQLModel, FastAPI, Django).\n Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).\n Familiarity with Python for Science : Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).\n Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.\n Experience with laboratory devices, robotics, or hardware drivers.\n \n \n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to","salary_min":144000,"salary_max":240000,"location":"Boston, MA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["agents","pytorch","robotics","data-pipeline","llm","embeddings","cloud","rag"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4248042009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T16:55:46Z","expires_at":"2026-06-29T14:17:43.519875Z","created_at":"2026-05-27T14:18:34.581118Z","updated_at":"2026-05-30T14:17:43.627321Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/77cc20d9-b485-408a-9a85-753c8c333d3c"},{"id":"81e447ea-83f4-4966-a2c8-0a0512efef5b","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Senior AI Engineer, Agent Harness","slug":"senior-ai-engineer-agent-harness-1c6d9f8f","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata is advancing the frontier of compliance automation by integrating intelligent AI capabilities into its trust platform. We are seeking a Senior AI Engineer to help design, build, and scale robust, high-impact AI systems that improve operational efficiency, enhance decision-making, and support trust-critical enterprise workflows.\n\nThis role focuses on solving complex, real-world problems with agentic AI, LLMs, and intelligent reasoning systems in a compliance and security context.\n\nAs a Senior AI Engineer, you will own the end-to-end design, implementation, and evolution of AI-driven features across the Drata platform.\n\nWhat you'll do:\n\nBuild Agentic \u0026 Intelligent AI Systems\n\n - Design and implement LLM-powered systems capable of multi-step reasoning, evidence grounding, and decision support in high-stakes compliance environments\n\n - Develop agentic workflows that combine retrieval, tool use, structured reasoning, and human oversight\n\n - Create interactive AI experiences that allow users to engage naturally with complex compliance and risk data\n\nAutomated Reasoning Over Regulations \u0026 Evidence\n\n - Build AI systems that reason over structured and unstructured data to support regulatory interpretation, control validation, and risk assessment\n\n - Ensure AI outputs are traceable, explainable, and auditable, meeting the expectations of enterprise compliance teams\n\nProduction-Grade AI Architecture\n\n - Architect and deploy scalable LLM + retrieval + agent systems in production environments\n\n - Optimize for latency, cost, reliability, and evaluation in real-world enterprise workloads\n\n - Partner with platform, security, product teams, and other application development teams to operationalize AI safely and effectively\n\nResponsible \u0026 Trustworthy AI\n\n - Embed human-in-the-loop workflows, confidence thresholds, and safety guardrails into AI systems\n\n - Ensure privacy-preserving data handling, robust failure modes, and transparent behavior aligned with Drata's values\n\nWhat you'll bring:\n\n - Experience: 5+ years of hands-on software engineering experience; 2+ years specifically in ML/AI engineering\n\n - Programming Languages: Proficiency in Python; TypeScript experience is a plus, especially for production AI system integration\n\n - Retrieval \u0026 Vector Stores: Familiarity with vector databases (Pinecone, Chroma, FAISS, etc.) and RAG system design\n\n - LLM \u0026 AI Systems: Proven experience building and shipping LLM-based applications in production, i","salary_min":166900,"salary_max":225900,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["llm","agents","rag","healthcare","embeddings"],"apply_url":"https://jobs.ashbyhq.com/drata/374b4418-aa4c-4005-812e-76a450c61476/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:24:52.13Z","expires_at":"2026-06-29T14:13:56.699213Z","created_at":"2026-05-27T14:14:32.675788Z","updated_at":"2026-05-30T14:13:56.815439Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/81e447ea-83f4-4966-a2c8-0a0512efef5b"},{"id":"96ba0be2-0b27-42c5-bc86-c4ffbb0b4359","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Applied Research Engineer","slug":"applied-research-engineer-8d39811c","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata is seeking an Applied Research Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research.\n\nThis is a research-focused role emphasizing experimentation and rigor over production engineering. You'll own the science behind how Drata's AI products retrieve, reason, and respond — and you'll work closely with AI and Software Engineers to turn validated approaches into production-ready systems.\n\nDrata's compliance platform is document-heavy: VRM Agent, AIQA, Trust Agent, policy-to-control mappers, and more all depend on high-quality information retrieval and reasoning.\n\nWhat you'll do:\n\n - Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, semantic routing\n\n - Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements ↔ evidence)\n\n - Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and structured prediction\n\n - Build and maintain evaluation frameworks: golden datasets, automated quality metrics, regression detection\n\n - Implement and tune ranking/reranking systems: cross-encoders, LLM-based rerankers, learning-to-rank, custom scoring functions\n\n - Run experiments to validate hypotheses and quantify improvements before production rollout\n\n - Debug failure modes and build error taxonomies across retrieval, reasoning, and generation\n\n - Collaborate with AI and Software Engineers to hand off validated approaches for productionization\n\n - Stay current on applied research in RAG, agents, LLM evaluation, and relevance modeling; bring innovations into the product\n\nWhat you'll bring:\n\n - 3+ years of experience in applied research, data science, or ML with a focus on NLP, information retrieval, or knowledge systems\n\n - 1+ years of hands-on experience building or contributing to production AI/ML systems\n\n - Strong foundation in information retrieval: dense and sparse retrieval, embedding models, search relevance\n\n - Experience with RAG systems: chunking strategies, vector databases, retrieval optimization\n\n - Proficiency in evaluation methodology: metrics design, golden dataset creation, A/B testing, statistical significance\n\n - Strong Python skills and comfort with notebook-driven research workflow","salary_min":145200,"salary_max":196400,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"mid","tags":["rag","generative-ai","embeddings","search","llm","nlp","agents","healthcare"],"apply_url":"https://jobs.ashbyhq.com/drata/51a418d1-c371-4f9f-b248-2c3b542bec42/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:24:47.784Z","expires_at":"2026-06-29T14:13:57.088082Z","created_at":"2026-05-27T14:14:33.116975Z","updated_at":"2026-05-30T14:13:57.199158Z","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/96ba0be2-0b27-42c5-bc86-c4ffbb0b4359"},{"id":"cb6155b3-db5f-4d05-a1db-f321ee0718be","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Senior Applied Research Engineer 2","slug":"senior-applied-research-engineer-2-fcdd01a9","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata is seeking a Senior Applied Research Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research.\n\nThis is a research-focused role emphasizing experimentation and rigor over production engineering. You'll own the science behind how Drata's AI products retrieve, reason, and respond — and you'll work closely with AI and Software Engineers to turn validated approaches into production-ready systems.\n\nDrata's compliance platform is document-heavy: VRM Agent, AIQA, Trust Agent, policy-to-control mappers, and more all depend on high-quality information retrieval and reasoning.\n\nWhat you'll do:\n\n - Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, semantic routing\n\n - Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements ↔ evidence)\n\n - Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and structured prediction\n\n - Build and maintain evaluation frameworks: golden datasets, automated quality metrics, regression detection\n\n - Implement and tune ranking/reranking systems: cross-encoders, LLM-based rerankers, learning-to-rank, custom scoring functions\n\n - Run experiments to validate hypotheses and quantify improvements before production rollout\n\n - Debug failure modes and build error taxonomies across retrieval, reasoning, and generation\n\n - Collaborate with AI and Software Engineers to hand off validated approaches for productionization\n\n - Stay current on applied research in RAG, agents, LLM evaluation, and relevance modeling; bring innovations into the product\n\nWhat you'll bring:\n\n - 6+ years of experience in applied research, data science, or ML with a focus on NLP, information retrieval, or knowledge systems\n\n - 2+ years of hands-on experience building or contributing to production AI/ML systems\n\n - Strong foundation in information retrieval: dense and sparse retrieval, embedding models, search relevance\n\n - Experience with RAG systems: chunking strategies, vector databases, retrieval optimization\n\n - Proficiency in evaluation methodology: metrics design, golden dataset creation, A/B testing, statistical significance\n\n - Strong Python skills and comfort with notebook-driven research wo","salary_min":192000,"salary_max":259800,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["rag","llm","generative-ai","healthcare","nlp","agents","embeddings","search"],"apply_url":"https://jobs.ashbyhq.com/drata/e66701e1-f52f-471b-9bcc-400e874c651c/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:24:39.187Z","expires_at":"2026-06-29T14:13:56.779385Z","created_at":"2026-05-27T14:14:32.761406Z","updated_at":"2026-05-30T14:13:56.891705Z","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/cb6155b3-db5f-4d05-a1db-f321ee0718be"},{"id":"4ed2ca6e-f534-411e-b47e-bc955d32008f","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Staff Applied Research Engineer","slug":"staff-applied-research-engineer-b2f192cc","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata, at the vanguard of compliance software innovation and renowned for its commitment to trust and security across the internet, is on an ambitious path to redefine how AI and General AI technologies bolster compliance automation.\n\nDrata is seeking an Applied AI Engineer to drive the quality and effectiveness of our AI systems through rigorous research, experimentation, and evaluation. In this role, you will optimize retrieval strategies, build evaluation frameworks, and establish the scientific foundation that enables our AI features to deliver accurate, trustworthy results.\n\nThis is a research-focused role emphasizing experimentation and rigor over production engineering. You'll work closely with AI Engineers handing off validated approaches for them to productionize while owning the quality metrics and evaluation systems that ensure our AI delivers on its promises.\n\nDrata's compliance platform is document-heavy: VRM Agent, AIQA, Trust Agent, policy-to-control mappers, and regulatory summarization all depend on retrieving the right information from large document sets. Your work will directly impact how well our AI understands and navigates compliance artifacts.\n\nWhat you'll do:\n\n - Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, structured retrieval, tool use, and multi-step workflows\n\n - Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements)\n\n - Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and weak supervision\n\n - Build and maintain evaluation frameworks: golden datasets, automated quality metrics, regression detection\n\n - Implement and tune ranking/reranking systems: cross-encoders, LLM-based rerankers, learning-to-rank, custom scoring functions\n\n - Run experiments to validate hypotheses and quantify improvements before production rollout\n\n - Debug failure modes and build error taxonomies across retrieval, reasoning, and generation\n\n - Collaborate with AI and Software Engineers to hand off validated approaches for productionization\n\n - Stay current on applied research in RAG, agents, LLM evaluation, and relevance modeling; bring innovations into the product\n\nWhat you'll bring:\n\n - 10+ years of experience in applied research, data science, or ML ","salary_min":220800,"salary_max":298800,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["search","embeddings","rag","healthcare","agents","generative-ai","nlp","llm"],"apply_url":"https://jobs.ashbyhq.com/drata/5fe5bc38-678d-468f-a762-a2144e88e45e/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:23:45.786Z","expires_at":"2026-06-29T14:13:56.857373Z","created_at":"2026-05-27T14:14:32.846263Z","updated_at":"2026-05-30T14:13:56.969043Z","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/4ed2ca6e-f534-411e-b47e-bc955d32008f"},{"id":"83ca8ffa-09ac-4942-a639-4e6c4b482642","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Senior Software Engineer, Operations Research","slug":"senior-software-engineer-operations-research-e517b660","description":"Your Impact at LILA \n We are a cross-functional team (Software and Robotics) developing orchestration algorithms (instrument scheduling and robot routing) and lab simulation capabilities. We are building the muscles of the lab, which translate the AI brain's ideas into efficient robotic movements. Our work involves building data pipelines to feed the orchestration algorithms. We work with robotics scientists to build and deploy the algorithms on our software platform and ensure they meet scientific constraints.\n We are seeking a Senior Software Engineer, Operations Research to join our software group and help build the next generation AI-driven scientific platform. In this role, you will design, build, and optimize backend systems and data infrastructure that power orchestration and lab execution. You will focus on developing services, high-performance APIs, databases, and ensuring the reliability of systems that integrate advanced AI frameworks with complex scientific workflows.\n You'll work closely with robotics researchers, platform engineers, and scientists to develop systems that can handle diverse workloads and scale to demanding throughput. This is an opportunity to apply your engineering expertise to a cutting-edge AI platform with real scientific impact. If you are passionate about building performant and elegant systems, we would love to hear from you.\n What You'll Be Building \n \n (Fleet) orchestrator, Scheduler, Manufacturing Execution System, data pipelines, and related software systems.\n Design \u0026 Build APIs: Design and build APIs and backend services that integrate with AI-driven applications, with focus on reliability and performance.\n Database Architecture \u0026 Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.\n Application Development: Drive the implementation of backend services, focusing on performance, maintainability, and reliability.\n Performance \u0026 Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.\n Cloud \u0026 Infrastructure: Build and deploy production-grade systems on AWS using Kubernetes and modern DevOps practices.\n Cross-Functional Collaboration: Work with robotics scientists, platform engineers, and ML teams to integrate data pipelines and orchestration into scientific workflows.\n \n What You'll Need to Succeed \n \n Bachelor's or Master's degree in Computer Science, Engineering, or related field.\n 5–10 years of engineering experience building and deploying large-scale backend or data systems in production.\n Backend / Data Development: Experience developing distributed software and data systems (Postgres, Flyte, Temporal, NATS/MQTT, FastAPI).\n Hands-on experience using AI coding assistants to drive productivity is required.\n Communication \u0026 Collaboration: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving: Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Experience developing scheduling software or manufacturing execution systems.\n Experience with operations research solvers (OR-Tools, HiGHS, Gurobi).\n Cloud \u0026 DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).\n Familiarity with Python for Science: Familiarity with data science, data visualization, and ML libraries (pandas, polars, numpy, scipy, pytorch).\n Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.\n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.\n Expected Base Salary Range\n $180,000 — $256,000 USD \n About LILA \n Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA bui","salary_min":180000,"salary_max":256000,"location":"Boston, MA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["pytorch","robotics","cloud","data-pipeline","embeddings","research"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4246973009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:22:46Z","expires_at":"2026-06-29T14:17:43.904427Z","created_at":"2026-05-27T14:18:35.008145Z","updated_at":"2026-05-30T14:17:44.01629Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/83ca8ffa-09ac-4942-a639-4e6c4b482642"},{"id":"25353da4-ae66-4acf-b4b6-fea4e00fda29","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Senior Software Engineer, Data","slug":"senior-software-engineer-data-e29e2009","description":"Your Impact at LILA \n Join us in shaping the future of science! We are seeking Senior Software Engineers with backend experience to join our Data Platform Team (Data), where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!\n About The Team \n The Data Platform Team (Data) builds and support the data systems that underpins Lila's AI Science Factory™. Every experiment run in our labs, every measurement from an instrument, and every signal from our operational systems flows through the platform they build. Their work spans real-time ingestion, large-scale analytical storage, workflow orchestration, and the self-service tools scientists, engineers, and ML teams use to go from raw measurements to discoveries. They build the data backbone of Scientific Superintelligence™, so the science moves faster and each experiment makes the next one smarter.\n What You'll Be Building \n \n Design \u0026 Build APIs: Design and build high-performance, secure, and well-documented APIs that integrate with AI-driven applications.\n Database Architecture \u0026 Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.\n Performance \u0026 Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.\n Cloud \u0026 Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.\n Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.\n \n What You'll Need To Succeed \n \n Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.\n 5-8+ years of engineering experience building and deploying large-scale backend systems in production.\n Cloud \u0026 DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).\n Experience with ORMs: Experience with and web services for CRUD services (SQL Alchemy, SQLModel, FastAPI, Django).\n Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).\n Full Stack Development : Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)\n Hands on experience using AI coding assistants to drive productivity is required.\n Communication \u0026 Collaboration : Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving : Proven ability to deliver backend solutions, balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Familiarity with Python for Science : Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).\n Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.\n Experience with laboratory devices, robotics, or hardware\n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.\n Expected Base Salary Range\n $144,000 — $288,000 USD \n About LILA \n Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.\n LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.\n Guided by our core values ","salary_min":144000,"salary_max":288000,"location":"Boston, MA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["robotics","data-pipeline","pytorch","cloud","embeddings"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4250077009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:22:23Z","expires_at":"2026-06-29T14:17:43.668505Z","created_at":"2026-05-27T14:18:34.759394Z","updated_at":"2026-05-30T14:17:43.783774Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/25353da4-ae66-4acf-b4b6-fea4e00fda29"},{"id":"4ba5f31d-5017-4850-9d40-5a3c0331575c","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Senior Software Engineer, Lab Software","slug":"senior-software-engineer-lab-software-347521f8","description":"Your Impact at LILA \n Join us in shaping the future of science! We are seeking Senior Software Engineers with backend experience to join our Lab Software Team (LaS), where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!\n About The Team \n The Lab as Software Team (LaS) acts as the physical and virtual execution layer for Lila's AI-driven science. This connects the Lila App to AI Science Factories (AISFs), the mechanism through which experiments are dispatched to real instruments. This team owns the full stack of lab integration: orchestration of labflows, instrument integrations, bi-directional data transfer, and the UI/UX that AI scientists and operators use to interact with the lab.\n What You'll Be Building \n \n Design \u0026 Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.\n Database Architecture \u0026 Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.\n Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.\n Performance \u0026 Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.\n Cloud \u0026 Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.\n Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.\n \n What You'll Need To Succeed \n \n Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.\n 5-8+ years of engineering experience building and deploying large-scale systems in production. You must be strong in backend.\n Full Stack Development : Experience developing web apps across the full stack (React, TypeScript, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)\n Hands on experience using AI coding assistants to drive productivity is required.\n Communication \u0026 Collaboration : Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving : Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Domain Background: Exposure to laboratory software for life sciences, material sciences, or related fields.\n Lab Automation Experience: Experience with laboratory devices, robotics, or hardware drivers.\n Orchestration Systems: Experience with software orchestration platforms (Airflow, Prefect, Temporal, Dagster) and design patterns\n Cloud \u0026 DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).\n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.\n Expected Base Salary Range\n $144,000 — $210,000 USD \n About LILA \n Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.\n LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.\n Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd ","salary_min":144000,"salary_max":210000,"location":"Boston, MA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["embeddings","data-pipeline","robotics","cloud"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4250038009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:22:02Z","expires_at":"2026-06-29T14:17:43.749222Z","created_at":"2026-05-27T14:18:34.838741Z","updated_at":"2026-05-30T14:17:43.859766Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4ba5f31d-5017-4850-9d40-5a3c0331575c"},{"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":"0344954d-9c09-460a-8b59-35f17075a617","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Software Engineer II, Lab Software","slug":"software-engineer-ii-lab-software-9b54dc8d","description":"Your Impact at LILA \n Join us in shaping the future of science! We are seeking a Software Engineer II with backend experience to join our Lab Software Team (LaS), where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!\n About The Team \n The Lab as Software Team (LaS) acts as the physical and virtual execution layer for Lila's AI-driven science. This connects the Lila App to AI Science Factories (AISFs), the mechanism through which experiments are dispatched to real instruments. This team owns the full stack of lab integration: orchestration of labflows, instrument integrations, bi-directional data transfer, and the UI/UX that AI scientists and operators use to interact with the lab.\n What You'll Be Building \n \n Design \u0026 Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.\n Database Architecture \u0026 Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.\n Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.\n Performance \u0026 Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.\n Cloud \u0026 Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.\n Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.\n \n What You'll Need To Succeed \n \n Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.\n 2-5 years of engineering experience building and deploying large-scale systems in production. You must be strong in backend.\n Full Stack Development : Experience developing web apps across the full stack (React, TypeScript, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)\n Hands on experience using AI coding assistants to drive productivity is required.\n Communication \u0026 Collaboration : Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving : Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Domain Background: Exposure to laboratory software for life sciences, material sciences, or related fields.\n Lab Automation Experience: Experience with laboratory devices, robotics, or hardware drivers.\n Orchestration Systems: Experience with software orchestration platforms (Airflow, Prefect, Temporal, Dagster) and design patterns\n Cloud \u0026 DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions)\n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.\n Expected Base Salary Range\n $120,000 — $180,000 USD \n About LILA \n Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.\n LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.\n Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love ","salary_min":120000,"salary_max":180000,"location":"Boston, MA","workplace":"onsite","job_type":"full-time","experience_level":"junior","tags":["robotics","embeddings","data-pipeline","cloud"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4250045009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-21T22:35:47Z","expires_at":"2026-06-29T14:17:43.982143Z","created_at":"2026-05-27T14:18:35.097887Z","updated_at":"2026-05-30T14:17:44.100354Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0344954d-9c09-460a-8b59-35f17075a617"},{"id":"68feb16e-e233-4a79-b299-d937608e7259","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Sr Principal/Principal Software Engineer, App","slug":"sr-principalprincipal-software-engineer-app-9d3ecfa0","description":"Your Impact at LILA Scientists shouldn't have to context-switch between a dozen tools to go from hypothesis to result. We're building the platform that makes this a reality — and we need engineers who want to solve problems no one has solved before.\n We're hiring Sr Principal / Principal Software Engineers to design the agents, interfaces, and platform integrations that let researchers seamlessly collaborate with AI.\n About The Team \n The Application Team sits at the center of LILA — the integration point where Machine Learning, Life Sciences, Physical Sciences, and Software become one AI-native experience that carries a scientist from hypothesis to experiment to breakthrough results.\n \n AI isn't a feature here — it's the architecture. Agent frameworks, tools, and LLM orchestration are core primitives, not bolt-ons.\n The problems are genuinely hard. Connecting AI to automated lab workflows, ML pipelines, and multi-domain knowledge graphs means inventing patterns, not copying them.\n You'll learn domains you never expected. Working shoulder-to-shoulder with lab scientists and ML engineers means your technical surface area grows fast.\n You'll ship things that matter. The tools you build accelerate research timelines from months to days.\n \n If you want to build at the intersection of AI and science, move fast without breaking trust, and grow into the kind of engineer who can architect systems that don't exist yet — we want to talk.\n What You'll Be Building \n \n Design \u0026 Build UI and APIs:  Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.\n Database Architecture \u0026 Scaling:  Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.\n Application Development:  Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.\n Performance \u0026 Reliability:  Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.\n Cloud \u0026 Infrastructure:  Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.\n Cross-Functional Collaboration:  Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.\n \n What You'll Need To Succeed \n \n Bachelor’s or Master’s degree  in Computer Science, Engineering, or related field.\n 8-15 years of engineering experience  building and deploying large-scale systems in production. You must be strong in either front-end or backend.\n Full Stack Development : Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)\n Hands on experience using AI coding assistants to drive productivity is required.\n Communication \u0026 Collaboration : Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving : Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Applied AI Engineering: Experience building with AI agents, graph-based workflows, tool-use protocols (MCP), RAG pipelines, or LLM orchestration frameworks.\n Cloud \u0026 DevOps Knowledge:  Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).\n Experience with ORMs:  Experience with and web services for CRUD services (SQLModel, FastAPI, Django).\n Orchestration Systems:  Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).\n Familiarity with Python for Science : Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).\n Domain Background:  Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.\n Experience with laboratory devices, robotics, or hardware drivers.\n \n  \n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based ","salary_min":204000,"salary_max":348000,"location":"Boston, MA","workplace":"onsite","job_type":"full-time","experience_level":"principal","tags":["llm","agents","cloud","rag","pytorch","robotics","data-pipeline","embeddings"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4248036009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-21T22:35:34Z","expires_at":"2026-06-29T14:17:44.397218Z","created_at":"2026-05-27T14:18:35.513932Z","updated_at":"2026-05-30T14:17:44.520714Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/68feb16e-e233-4a79-b299-d937608e7259"},{"id":"1494fe7f-f004-4ea4-b79f-4bcda66b374f","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Staff Software Engineer, Lab Software","slug":"staff-software-engineer-lab-software-a163f70b","description":"Your Impact at LILA \n Join us in shaping the future of science! We are seeking Staff Software Engineers with backend experience to join our Lab Software Team (LaS), where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!\n About The Team \n The Lab as Software Team (LaS) acts as the physical and virtual execution layer for Lila's AI-driven science. This connects the Lila App to AI Science Factories (AISFs), the mechanism through which experiments are dispatched to real instruments. This team owns the full stack of lab integration: orchestration of labflows, instrument integrations, bi-directional data transfer, and the UI/UX that AI scientists and operators use to interact with the lab.\n What You'll Be Building \n \n Design \u0026 Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.\n Database Architecture \u0026 Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.\n Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.\n Performance \u0026 Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.\n Cloud \u0026 Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.\n Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.\n \n What You'll Need To Succeed \n \n Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.\n 8+ years of engineering experience building and deploying large-scale systems in production. You must be strong in backend.\n Full Stack Development : Experience developing web apps across the full stack (React, TypeScript, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)\n Hands on experience using AI coding assistants to drive productivity is required.\n Communication \u0026 Collaboration : Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving : Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Domain Background: Exposure to laboratory software for life sciences, material sciences, or related fields.\n Lab Automation Experience: Experience with laboratory devices, robotics, or hardware drivers.\n Orchestration Systems: Experience with software orchestration platforms (Airflow, Prefect, Temporal, Dagster) and design patterns\n Cloud \u0026 DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).\n \n \n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.\n Expected Base Salary Range\n $192,000 — $256,000 USD \n About LILA \n Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.\n LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.\n Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd","salary_min":192000,"salary_max":256000,"location":"Boston, MA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["embeddings","robotics","cloud","data-pipeline"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4250063009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-21T22:35:19Z","expires_at":"2026-06-29T14:17:44.893063Z","created_at":"2026-05-27T14:18:36.013907Z","updated_at":"2026-05-30T14:17:45.013487Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/1494fe7f-f004-4ea4-b79f-4bcda66b374f"},{"id":"a9b04ca5-e47c-493e-beea-c98f715ff641","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Staff Software Engineer, Scientific System of Record","slug":"staff-software-engineer-scientific-system-of-record-cdd3fc1a","description":"Your Impact at LILA \n We are seeking a Staff Software Engineer to join our Scientific System of Record Team and help build the next-generation AI-driven scientific platform.\n You will focus on developing user interfaces, services, high-performance APIs, databases, and reliable systems that integrate advanced AI frameworks with complex scientific analytics and laboratory workflows. You’ll work closely with ML researchers, platform engineers, and scientists to develop systems that can handle diverse workloads and scale seamlessly, including structured SQL databases, data lakehouses, workflow engines, and lab execution environments.\n This is an opportunity to apply your deep front-end and backend expertise to a cutting-edge AI platform with real scientific impact. If you are passionate about building performant, elegant systems, we would love to hear from you.\n About The Team \n The Scientific System of Record Team (SSR) builds the memory layer for Lila's operations. It answers two questions: what did we plan to build? and what actually happened? These systems connect scientific intent to physical reality. Together with the data and automation teams, their systems ensure reproducibility and close the Design-Build-Test-Learn (DBTL) loop.\n What You'll Be Building \n \n User Interfaces and APIs: Design and build high-performance, secure, and well-documented UIs and APIs that integrate with AI-driven applications.\n Database Architecture and Scaling: Develop schemas and manage diverse data systems, including SQL, NoSQL, vector databases, and other emerging technologies, for performance and scalability.\n Application Development: Drive implementation of front-end and backend services with a focus on performance, maintainability, and reliability.\n Performance and Reliability: Diagnose and resolve system bottlenecks while ensuring high availability and low-latency performance across large-scale workloads.\n Cloud and Infrastructure: Leverage AWS services, Kubernetes, and modern DevOps practices to build and deploy production-grade systems at scale.\n Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.\n \n What You’ll Need to Succeed \n \n Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.\n 6–8+ years of engineering experience building and deploying large-scale systems in production.\n Strong expertise in at least one of the following areas, with the ability to work across the stack: front-end engineering, backend engineering, or data modeling and system design.\n TypeScript, React, and Python: Strong experience with React and TypeScript is required; Python experience is strongly preferred.\n Databases: Strong experience with SQL, NoSQL, and emerging database technologies such as vector databases; proven track record in schema design, indexing, and query optimization.\n API Development: Proven ability to design and scale RESTful or GraphQL APIs with a focus on reliability and performance.\n Hands-on experience using AI coding assistants to improve engineering productivity.\n Scientific or Data-Intensive Domains: Experience working in life sciences, materials science, or other research-heavy or data-intensive fields.\n Communication and Collaboration: Strong listening skills and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving: Proven ability to take ownership of complex technical challenges while balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Cloud and DevOps: Hands-on experience with AWS, GCP, or Azure; strong understanding of Kubernetes, containerization, infrastructure as code such as Terraform or CloudFormation, and CI/CD pipelines such as GitHub Actions.\n Orchestration Systems: Experience with orchestration tools such as Flyte, Temporal, Airflow, Prefect, or similar systems.\n Experience building laboratory, scientific workflow, LIMS, ELN, data platform, or ML platform products.\n Experience designing systems that support auditability, traceability, reproducibility, data provenance, or regulated workflows.\n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to","salary_min":144000,"salary_max":288000,"location":"Boston, MA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["embeddings","api-design","data-pipeline","cloud"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4248045009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-21T22:33:04Z","expires_at":"2026-06-29T14:17:44.978763Z","created_at":"2026-05-27T14:18:36.116567Z","updated_at":"2026-05-30T14:17:45.092909Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a9b04ca5-e47c-493e-beea-c98f715ff641"},{"id":"3a790011-3259-4ddc-b03a-1e3227951d9b","company_id":"c587b06c-b6f0-4d1d-b694-6fb6abc2a6bb","title":"Forward Deployed Engineer","slug":"forward-deployed-engineer-988ebd0a","description":"Who We Are \n Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.\n Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.\n We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.\n  \n What We Are Looking For \n We are seeking an experienced  Forward Deployed Engineer  to partner directly with customers to architect, build, and deploy production AI systems and workflows on Lightning AI’s platform. In this role, you will own the customer journey from early exploration through production deployment, translating ambiguous business goals into reliable, observable systems with clear quality, latency, scalability, and cost outcomes.\n This role sits at the intersection of software engineering, research engineering, AI infrastructure, product thinking, and customer engagement. You’ll work closely with customer engineering teams as well as Lightning’s internal product and engineering organizations to deliver production-ready AI systems that help customers realize value quickly and scale with confidence.\n This is a hands-on engineering role that combines software development, AI infrastructure, technical customer engagement, and product thinking. Successful candidates will be  highly technical, customer-oriented builders who thrive in fast-moving environments and enjoy solving ambiguous, real-world AI systems problems.\n This role is based in one of our hubs (New York City, San Francisco, Seattle, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. \n What You'll Do \n \n Partner directly with customers to design, implement, and deploy end-to-end AI systems and workflows on Lightning’s platform\n Translate vague customer objectives into clear technical specifications, proof-of-concepts, and scalable production implementations\n Own customer technical engagements end-to-end, from early discovery and architecture through deployment, monitoring, and expansion\n Develop and maintain production-grade software systems and services using modern programming languages, with a strong preference for Python\n Build reliable, observable systems with strong attention to latency, throughput, quality, scalability, and cost efficiency in production environments\n Debug and optimize AI systems across inference infrastructure, model behavior, APIs, and distributed workloads to improve performance and reliability\n Work closely with customer engineering teams throughout the full lifecycle of AI deployments, including technical discovery, implementation, deployment, and scaling\n Collaborate cross-functionally with Lightning’s product and engineering teams to improve platform capabilities, influence roadmap priorities, and identify opportunities for reusable product improvements\n Navigate ambiguity with sound technical judgment, making thoughtful tradeoffs and selecting the right tools and approaches without introducing unnecessary complexity\n Demonstrate strong ownership and accountability in execution, with a commitment to delivering high-quality outcomes for both customers and internal teams\n \n What You’ll Need \n Required Qualifications \n \n Strong software engineering experience building and maintaining production systems in one or more general-purpose programming languages, with Python strongly preferred\n Experience working directly with customers in highly technical environments, such as Forward Deployed Engineering, Solutions Engineering, Applied AI Engineering, Technical Product Engineering, or related roles\n Familiarity with AI/ML pipelines and the lifecycle of model development, evaluation, deployment, and monitoring\n Experience deploying and operating production AI/ML systems in cloud or distributed environments\n Familiarity with modern AI infrastructure and tooling such as Docker, Kubernetes, APIs, model serving systems, or distributed inference workloads\n Strong communication and collaboration skills, especially when working through complex technical topics with customers, engineers, and cross-functional stakeholders\n Ability to translate business needs into technical solutions and drive projects from initial concept through production delivery\n Ability to execute effectively in ambiguous, fast-moving, high-growth environments\n Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field\n \n Nice-to-Haves \n \n Experience building, deploying, or optimizing large-scale AI/ML","salary_min":120000,"salary_max":250000,"location":"London, UK","workplace":"hybrid","job_type":"full-time","experience_level":"mid","tags":["distributed-systems","fine-tuning","pytorch","embeddings","search","llm","mlops"],"apply_url":"https://job-boards.greenhouse.io/lightningai/jobs/7742081003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-21T17:15:55Z","expires_at":"2026-06-29T14:03:02.726355Z","created_at":"2026-05-27T14:03:14.78242Z","updated_at":"2026-05-30T14:03:02.834329Z","company_name":"Lightning AI","company_slug":"lightning-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=lightning.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3a790011-3259-4ddc-b03a-1e3227951d9b"}],"page":1,"per_page":20,"total":291,"total_pages":15}