Forward Deployed Engineer (FDE), Healthcare - SF
Application analysis
Forward Deployed Engineer (FDE), Healthcare - SF at OpenAI is a forward deployed ai research lab role for engineers who want customer-facing technical work with real deployment ownership.
Reading this role
This Forward Deployed Engineer role centers on embedded customer delivery — discovery, prototyping, integration, and production rollout. Key signals from the listing: Senior scope.
About OpenAI
OpenAI ships frontier models to real customers through small, high-trust engineering teams. Forward deployed roles sit between product, research, and enterprise buyers. The role is anchored in San Francisco, so expect on-site customer work in that region.
Signals in the listing
Stand out for Forward Deployed Engineer (FDE), Healthcare - SF
- Lead your application with one paragraph tying Forward Deployed Engineer (FDE), Healthcare - SF to a specific customer or deployment you owned — OpenAI hires for shipped outcomes, not tool lists.
- Prepare a 5-minute “week one on site” plan: who you would meet, what you would inspect in their stack, and what artifact you would deliver by day five.
- Show you can go from discovery notes → working integration → production checklist without needing a large internal team.
- This role is tied to San Francisco — mention willingness to work on-site with customers and any existing ties to that market (clients, partners, or domain knowledge).
Stand out at OpenAI
- Demonstrate customer obsession with safety constraints with a concrete example — OpenAI will probe for specifics, not buzzwords.
- Demonstrate writing and communication with a concrete example — OpenAI will probe for specifics, not buzzwords.
- Interview loops emphasize problem decomposition, taste in product, and whether you can earn trust with technical and non-technical stakeholders quickly.
- Read recent engineering blog posts, product launches, and customer stories on openai.com — reference one explicitly in your outreach to show genuine interest.
Tailored from this listing’s title, company, and description. Always verify requirements on the company careers page before applying.
Role description
About the Team OpenAI’s Forward Deployed Engineering team partners with healthcare organizations to deploy production AI systems across clinical, operational, and member-facing workflows. We work at the boundary of customer deployment and core platform development, using customer engagements to define repeatable architectures, evaluations, integrations, and operating standards for complex, regulated healthcare environments. About the Role We are hiring a Forward Deployed Engineer (FDE) to own end-to-end deployments of our models within healthcare organizations, including payers, providers, health systems, and healthcare technology companies. You will lead technical discovery, architecture, implementation, evaluation, productionization, and handoff, translating complex customer workflows, data, infrastructure, and regulatory constraints into production AI systems. You will measure success through production adoption, measurable workflow impact, and evaluation loops that establish customer-specific benchmarks, acceptance criteria, and launch readiness. You’ll collaborate directly with customer technical and operational teams, alongside internal Business, Research, Product, Engineering, and Security partners, to deliver solutions and translate deployment learnings into product improvements. This role owns the technical solution; ownership of the commercial or executive relationship is not required. 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. Travel up to 50% is required. In this role, you will: - Own the technical solution end to end, from customer discovery and workflow scoping through architecture, hands-on implementation, evaluation, production deployment, adoption, and handoff. - Partner credibly with customer engineers, operators, and domain experts to frame ambiguous problems, define scope, and translate payer, provider, or health-system workflows into technical