Forward Deployed Engineer (FDE), Life Sciences - SF
San Francisco, CA · HybridFull-time$185–300K/yrPosted todayStill listed today
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At a glance
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Job overview
OpenAI’s Forward Deployed Engineering team partners with life sciences organizations and research institutions to deploy AI systems across research and development. The engineer leads end-to-end customer deployments, translating scientific and operational workflows into production systems, measuring adoption and impact, and using evaluation feedback to inform product and model roadmaps. The role is based in San Francisco, follows a hybrid model with three office days per week, and requires up to 50% travel.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
About the team OpenAI’s Forward Deployed Engineering team partners with global pharma and biotech, CROs, and research institutions to deploy existing expertise across the R&D value chain to help customers design and ship production-grade AI systems. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments. About the role We are hiring a Forward Deployed Engineer (FDE) to push the frontier on what is possible today across drug discovery (e.g., target identification, molecular design, pre-clinical) and development (e.g., trial design, trial ops, biostats) by leading end-to-end deployments of our models inside life sciences organizations and research institutions. You will work with customers who are deep experts in their scientific or operational domains, translating real-world data, infrastructure, and constraints into production systems. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback loops, including evaluation benchmarks and acceptance criteria, that inform product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM to deliver in regulated contexts, including inspection readiness with audit trails and traceable evidence. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role, you will:
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Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows.
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Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints.
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Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until we demonstrate sustained production impact.
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Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.
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Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes.
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Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.
You might thrive in this role if you:
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Bring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged.
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Have owned customer GenAI deployments end-to-end from scoping through production adoption, and improved them through evaluation design, error analysis, and iterative evidence generation that tightens acceptance criteria over time.
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Have delivered AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout.
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Communicate clearly across scientific, clinical, model research, technical, and executive audiences, translating technical tradeoffs into decision quality, risk posture, and measurable outcomes with credibility.
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Apply systems thinking with high execution standards, consistently turning failures, escalations, and audit findings into improved operating standards, validation artifacts, and repeatable deployment playbooks.
About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link. OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
How this job compares
Set against the 2,926 open Forward Deployed Engineer jobs on Olive Jobs, counted November 7, 2026.
- Pay
- This posting$185–300K/yr
- California median$156–265K/yr558 salary ranges
- US median$140–265K/yr2,572 salary ranges
This range's midpoint, $243K, is 18% above the California median midpoint ($205K) — in the top quarter of Forward Deployed Engineer salary ranges in California.
- Openings
- Olive Jobs lists 675 open Forward Deployed Engineer jobs in California and 2,926 across the US. 6% of them nationwide are listed as remote or flexible.
- Experience
- Forward Deployed Engineer postings that state a minimum ask for 5 years of experience at the median; the middle half ask for 3 to 7 years (2,547 postings).
- Education
- 604 of the 2,926 open Forward Deployed Engineer jobs (21%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 7, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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