Manager, Forward Deployed Engineer (FDE), Life Sciences

OpenAISan Francisco, CA
4hHybrid

About The Position

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. 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. As a Life Sciences FDE Manager, you’ll lead a team of FDEs delivering production AI systems across drug discovery and development workflows. 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. 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. This role will require travel up to 25%.

Requirements

  • Bring 8+ years of engineering or technical delivery experience, including 2+ years managing high-performing customer-facing or systems-oriented engineering teams
  • Have led complex, high-pressure technical programs from prototype through sustained production use in regulated environments
  • Have 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 credibility
  • Turn field experience into precise, actionable feedback for Product, Research, and GTM teams

Responsibilities

  • 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 technical direction
  • Guide teams through ambiguous, multi-workstream engagements spanning data, workflows, infrastructure, security, and scientific stakeholders
  • Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks, then convert results into crisp roadmap input
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