Forward Deployed Engineer

AI research and deployment company building and deploying frontier AI products, including ChatGPT, Codex, and its API platform.

Recently funded151 current maintainers88 active leads20 new active leads99 lead step-downs12 early lead departures
San Francisco, United States
About OpenAI

OpenAI’s mission is to ensure artificial general intelligence benefits all of humanity. It consists of the nonprofit OpenAI Foundation and OpenAI Group, a public benefit corporation governed by the Foundation.

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Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will lead end-to-end deployments of frontier models, from discovery and technical scoping through system design, development, and production rollout. You will work directly with customer engineering and domain teams, build full-stack solutions, guide adoption, and share field feedback that improves products and models.

Requirements

  • Have 5+ years of engineering or technical deployment experience including customer-facing work.
  • Have scoped and delivered complex systems in fast-moving or ambiguous environments.
  • Write and review production-grade frontend and backend code using Python, JavaScript, or comparable stacks.
  • Have built or deployed systems powered by LLMs or generative models.
  • Understand how model behaviour affects product experience.
  • Communicate clearly with engineers, product teams, and customer stakeholders.

Responsibilities

  • Own technical delivery across multiple deployments from first prototype to stable production.
  • Build full-stack systems that deliver customer value and sharpen learning.
  • Embed with customer teams, understand their needs, and guide adoption of delivered solutions.
  • Scope work, sequence delivery, and remove blockers early.
  • Make trade-offs between scope, speed, and quality to protect delivery.
  • Contribute directly to code when progress or clarity depends on it.
  • Codify working patterns into reusable tools, playbooks, or building blocks.
  • Share field feedback to help Research and Product understand model performance and improvement opportunities.
  • Keep teams moving through clarity and follow-through.

Benefits

  • Relocation assistance.