engineering
Posted 4 days agoManager, Forward Deployed Engineer (FDE), Life Sciences
at openai
San Francisco, United StatesHybrid
Requirements
- About the team OpenAI’s Forward Deployed Engineering (FDE) team partners with global pharma and biotech, CROs, and research institutions to deploy production-grade AI systems across the R&D value chain.
- About the role As a Life Sciences FDE Manager, you’ll lead a team of FDEs delivering production AI systems across drug discovery and development workflows.
- In this role you will - Lead and grow a team of FDEs delivering production AI systems across regulated life sciences environments - Be accountable for your team’s end-to-end delivery outcomes, balancing scope, speed, robustness, and risk in high-stakes deployments - Coach and develop engineers through direct feedback, high technical standards, and clear expectations for execution and ownership - Operate as a player-coach, directly contributing to production systems while leading, coaching, and setting
- experience working in or adjacent to life sciences R&D, clinical research, scientific software, or regulated scientific data environments - Write and review production-grade code and can guide architectural decisions across backend, data, and ML-adjacent systems - Translate scientific and technical tradeoffs into clear delivery plans, risk posture, and measurable outcomes across scientific, clinical, technical, and executive audiences - Elevate team performance through clarity, judgment, and technical
- experience into precise, actionable feedback for Product, Research, and GTM teams About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence
Additional details
- 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.
- You’ll own delivery outcomes and team leverage while staying hands-on as a player-coach.
- This includes building and shipping alongside the team, setting technical direction, and maintaining a high bar for production-grade systems in regulated environments.
- We measure success through the health and quality of your FDE team, production adoption and measurable workflow impact, the quality of eval-driven feedback delivered back to Product and Research, and the repeatability of deployment patterns across life sciences customers.
- We use a hybrid work model of 3 days in the office per week.