Full-Stack Engineer, Enterprise AI Workflows

OpenAI

San Francisco (CA)

On-site

USD 293,000 - 325,000

Full time

9 days ago

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Job summary

OpenAI is seeking a full-stack product engineer for Enterprise Verticals in San Francisco. You will own end-to-end enterprise workflows, shaping the product, building across frontend and backend, and coordinating with platform teams.

You will work on ChatGPT Work surfaces, services, plugins, connectors, and data boundaries, making rollout observable with evaluations and clear fallback paths. Candidates turn customer evidence into scalable product decisions.

Qualifications

  • Experience building and operating full-stack production products across modern frontend and backend stacks.
  • Ability to design evolvable APIs, data models, and distributed systems with secure data flows and partial-failure behavior.
  • Experience owning production systems at scale with observability, testing, incident response, and safe migrations.

Responsibilities

  • Build and ship role-specific workflows across ChatGPT Work surfaces, services, plugins, and connectors.
  • Turn customer and design-partner evidence into clear product decisions, milestones, and measurable quality gates.
  • Partner with Design, Research, GTM, Security, and platform teams.
  • Create robust evaluations, observability, and rollback paths.
  • Own the full loop from prototype through bounded rollout and iteration.
  • Define explicit contracts and fallback paths with shared platform teams when a workflow depends on connectors, permissions, model routing, or other cross-team systems.

Job description

OpenAI is seeking a full-stack product engineer for Enterprise Verticals in San Francisco. You will own end-to-end enterprise workflows, shaping the product, building across frontend and backend, and coordinating with platform teams.

You will work on ChatGPT Work surfaces, services, plugins, connectors, and data boundaries, making rollout observable with evaluations and clear fallback paths. Candidates turn customer evidence into scalable product decisions.

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