Forward Deployed Engineer (FDE), Life Sciences - SF

OpenAI • San Francisco, CA

1d • Hybrid

About The Position

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role We are hiring a Forward Deployed Engineer (FDE) to lead end-to-end deployments of our models inside life sciences organizations and research institutions, from early R&D through clinical and operational workflows. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. 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.

Requirements

• Bring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; advanced degree or equivalent applied experience preferred in Biomedical Engineering, Computational Biology, Bioinformatics, or a related field
• Have owned customer GenAI deployments end-to-end from scoping through production adoption and improved them through evals, error analysis, and iteration
• Have delivered AI systems in trial design, regulatory writing, or scientific environments where validation, auditability, and compliance constraints shaped the system
• Communicate clearly across scientific, model research, technical, and executive audiences, translating technical concepts for non-technical stakeholders with credibility
• Apply systems thinking with high execution standards, consistently turning failures or escalations in regulated environments into new operating standards

Responsibilities

• Design and ship production systems around models, owning integrations, data flows, reliability, and on-call readiness
• Lead discovery and scoping from pre-sales through post-sales, including problem framing, constraints, trade-offs, and a delivery plan
• Define launch criteria for regulated contexts, outcome metrics, and drive adoption until you prove production impact
• Build in sensitive data environments where auditability, validation, and access controls drive architecture decisions
• Run evaluation loops that measure model and system quality in life science workflows to drive model and product improvements
• Distill production learnings into hardened primitives, reference architectures, and templated workflows that scale across regulated life sciences environments.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees