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OpenAI's Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems, operating at the intersection of customer delivery and core platform development.
In this role, you will lead complex end-to-end deployments of frontier AI models in production alongside OpenAI's most strategic customers. You own the full lifecycle: discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. Success is measured through production adoption, measurable workflow impact, and eval-driven feedback that shapes product and model roadmaps.
Key responsibilities include:
- Own technical delivery across multiple deployments from prototype to stable production
- Build full-stack systems that deliver customer value and inform product learning
- Embed closely with customer teams to understand needs and guide adoption
- Scope work, sequence delivery, and remove blockers early
- Make trade-offs between scope, speed, and quality while protecting delivery timelines
- Contribute directly to code when progress or clarity requires it
- Codify working patterns into tools, playbooks, and reusable building blocks
- Share field feedback that helps Research and Product teams understand model performance and improvement opportunities
- Keep teams moving through clarity and follow-through
You will work closely with Product, Research, Partnerships, GRC, Security, and GTM teams. The role is based in San Francisco with a hybrid work model (3 days in office per week). Travel up to 50% is required. OpenAI offers relocation assistance.
Requirements:
- 5+ years of engineering or technical deployment experience including customer-facing work
- Experience scoping and delivering complex systems in fast-moving or ambiguous environments
- Production-grade code writing and review across frontend and backend (Python, JavaScript, or comparable stacks)
- Experience building or deploying systems powered by LLMs or generative models, with understanding of how model behavior affects product experience
- Ability to simplify complexity and make fast, sound decisions under pressure
- Clear communication with engineers, product teams, and customer stakeholders
- Early risk spotting and adjustment capability without slowing momentum
- Calm judgment and composure when stakes are high
