AI Deployment Engineer, Ecosystem - Plugins

OpenAI OpenAI · AI Frontier · San Francisco, CA · Go To Market

AI Deployment Engineer focused on helping strategic partners build, evaluate, and launch high-utility plugins for ChatGPT and Codex. This role involves hands-on product engineering, partner engagement, and contributing to the platform itself, with a strong emphasis on user value, reliability, and developer experience.

What you'd actually do

  1. Own the technical partner journey for priority B2B plugins—from pitch and readiness assessment through architecture, build, evaluation, submission, launch, and ongoing maintenance.
  2. Identify strong plugin use cases, define crisp user journeys and expected behaviors, and help partners focus on workflows where ChatGPT or Codex can create meaningful user value.
  3. Write production and sample code, build prototypes and reference implementations, and create the technical guidance, evals, launch checklists, and debugging tools that move partners from concept to production.
  4. Debug API contracts, OAuth/login, tool invocation, latency, retries, rate limits, observability, data model, and user-experience issues across partner and OpenAI systems.
  5. Review partner architectures and implementation plans for API design, scopes and permissions, data handling, safety, privacy, reliability, and long-term maintainability.

Skills

Required

  • 4-6 years of professional software engineering experience
  • Strong technical skills for platform contribution and hands-on coding
  • Experience building and operating production APIs, backend services, developer platforms, apps, plugins, connectors, or integrations
  • Ability to reason across frontend, backend, auth, reliability, privacy, evaluations, and UX constraints
  • Strong product sense
  • Clear communication with external engineers, product leaders, executives, and internal cross-functional stakeholders
  • Ability to make ambiguous partner ideas concrete through runnable prototypes, API contracts, technical specs, and pragmatic implementation guidance
  • Comfortable reading unfamiliar code, making targeted platform changes, and debugging distributed systems
  • Care deeply about user trust, privacy, data handling, and product quality in AI-powered experiences
  • Balance urgency with judgment

Nice to have

  • Experience with OAuth/login flows, API design, webhooks, schemas, rate limits, observability, SDKs, and production launch operations
  • Prior customer-facing or partner-facing engineering experience
  • Familiarity with AI products, LLM APIs, tool calling, MCP, ChatGPT or Codex surfaces, developer platforms, or marketplace ecosystems
  • Comfortable making targeted changes across backend services, frontend surfaces, SDKs, docs, internal tools, or monorepo codebases
  • Strong written communication skills

What the JD emphasized

  • high-utility plugins
  • production-ready integrations
  • genuinely useful
  • production software
  • product quality in AI-powered experiences

Other signals

  • partner integrations
  • plugins
  • ChatGPT
  • Codex
  • evaluations
  • developer experience