About the job
Join OpenAI's innovative Forward Deployed Engineering team, where we collaborate with leading pharmaceutical and biotechnology companies, contract research organizations (CROs), and academic research institutions. Our mission is to leverage advanced AI technologies to enhance the R&D value chain, aiding our clients in designing and deploying robust AI solutions that meet production-grade standards. We thrive at the nexus of customer success and core platform development, transforming initial deployments into scalable systems and standardized evaluation practices suitable for regulated environments.
Role Description
We are seeking a skilled Forward Deployed Engineer (FDE) to redefine the boundaries of drug discovery and development, including target identification, molecular design, clinical trial design, and biostatistics. In this role, you will lead comprehensive deployments of our AI models within life sciences organizations and research institutions, bridging the gap between complex scientific domains and production-ready systems. Your expertise will be vital in translating real-world data and operational constraints into effective AI solutions.
Success in this role will be measured by the adoption of your solutions in production environments, the tangible impact on workflows, and the establishment of continuous feedback loops that utilize evaluation benchmarks to shape our product and model roadmaps. You will collaborate closely with teams across Product, Research, Partnerships, Governance, Risk and Compliance (GRC), Security, and Go-To-Market (GTM) to ensure successful delivery within regulated settings, maintaining inspection readiness with comprehensive audit trails and traceable evidence.
This position is based in New York City, following a hybrid work model requiring three days in the office each week. We offer relocation assistance, and travel may be required up to 50% of the time.
Key Responsibilities
Design and implement production systems centered around AI models, managing integrations, data provenance, reliability, and on-call support across research, clinical, and operational workflows.
Lead the discovery and scoping process from pre-sales to post-sales, translating ambiguous workflow requirements into hypothesis-driven problem statements, system specifications, and actionable plans with clear metrics for success.
Establish and enforce launch criteria for regulated environments, including validation documentation, audit preparedness, and outcome measurement, driving delivery until sustained production impact is achieved.
Develop systems within sensitive scientific data environments where auditability, validation, and access controls dictate system architecture, operational protocols, and failure management strategies.
Conduct evaluation cycles to assess model and system performance, ensuring continuous improvement and alignment with project goals.

