Manager, Forward Deployed Engineer (FDE), Life Sciences
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. We operate at the intersection of customer delivery and core platform development, converting early deployments into
What this role actually needs.
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. We operate at the intersection of customer delivery and core platform development, converting early deployments into 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 Company context: OpenAI builds frontier AI systems, research infrastructure, and applied products for developers, enterprises, and global users.
Day-to-day expectations
OpenAI lists these responsibilities for the Manager, Forward Deployed Engineer (FDE), Life Sciences role.
- 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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Source: jobs.ashbyhq.com · Source ID: 679cc2c7-e153-480b-8b9f-ecb69a19975a · Confidence: 97/100 · Last checked: May 7, 2026
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