Forward-Deployed Engineer (FDE), Life Sciences - San Francisco

Details

OpenAI’s Forward Deployed Engineering team partners with global pharma and biotech companies, CROs, and research institutions to deploy existing expertise across the R&D value chain and help customers design and ship production-grade AI systems. The team operates 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.

The role focuses on advancing drug discovery, including target identification, molecular design, and pre-clinical research, as well as development areas such as trial design, trial operations, and biostatistics. The Forward Deployed Engineer will lead end-to-end deployments of OpenAI models inside life sciences organizations and research institutions, translating real-world data, infrastructure, and operational constraints into production systems.

Success is measured through production adoption, measurable workflow impact, and evaluation-driven feedback loops, including evaluation benchmarks and acceptance criteria that inform product and model roadmaps. The role works closely with Product, Research, Partnerships, GRC, Security, and GTM teams to deliver systems in regulated contexts, including inspection readiness with audit trails and traceable evidence.

This role is based in San Francisco and follows a hybrid work model with three days in the office per week. Travel of up to 50% is required.

Responsibilities

• Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows.
• Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and execution plans with measurable endpoints.
• Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, and outcome metrics, and drive delivery until sustained production impact is demonstrated.
• Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.
• Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use the results to drive model and product changes.
• Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.

Requirements

• 5+ years of software engineering, machine learning engineering, or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software.
• A PhD, MS, or equivalent applied experience in a life sciences-relevant field is encouraged.
• Experience owning customer GenAI deployments end-to-end, from scoping through production adoption, and improving them through evaluation design, error analysis, and iterative evidence generation.
• Experience delivering AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout.
• Ability to communicate clearly across scientific, clinical, model research, technical, and executive audiences, translating technical tradeoffs into decision quality, risk posture, and measurable outcomes.
• Systems thinking and high execution standards, including the ability to turn failures, escalations, and audit findings into improved operating standards, validation artifacts, and repeatable deployment playbooks.

Benefits

• Base salary of $185,000–$300,000 per year.
• Equity, performance-related bonuses for eligible employees, and additional benefits.
• Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
• Pre-tax accounts for health and dependent care expenses, as well as commuter expenses.
• 401(k) retirement plan with employer match.
• Paid parental, medical, and caregiver leave.
• Paid time off, paid company holidays, office closures, and paid sick or safe time as required by applicable law.
• Mental health and wellness support.
• Employer-paid basic life and disability coverage.
• Annual learning and development stipend.
• Daily office meals and eligible meal delivery credits.
• Relocation support for eligible employees.