AI Deployment Engineer, Plugins

AI Deployment Engineer, Plugins

Technical Success - San Francisco

The Ecosystem AI Deployment Engineering (ADE) team supports strategic partners as they build high-quality technical integrations into ChatGPT and Codex. Our goal is to create products users depend on, drive adoption and retention, and build an ecosystem where partners win when OpenAI wins.

We are looking for an AI Deployment Engineer to help strategic partners design, build, evaluate, submit, launch, and maintain high-utility plugins for ChatGPT and Codex. This is a hands‑on, partner‑facing product engineering role for someone who can contribute to the platform itself, lead sophisticated partner engagements, and translate ambiguous product needs into production‑ready integrations.

You will work across partner product and engineering teams and OpenAI's product, engineering, partnerships, legal, policy, design, and go‑to‑market teams. You will identify the right use cases, prototype and review implementations, run evaluations, debug issues across systems, guide partners through submission and review, and support launch and post‑launch iteration. The best person for this role moves fluidly between code, product judgment, project leadership, and clear communication with engineers and executives.

This role is a fit for a product‑minded engineer who wants to stay close to users and partners while still going deep on code, reliability, evaluations, and developer experience. The goal is to help partners ship plugins that are not merely technically functional, but genuinely useful in ChatGPT and Codex.

This role is based in our San Francisco office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

• Own the technical partner journey for priority B2B plugins—from pitch and readiness assessment through architecture, build, evaluation, submission, launch, and ongoing maintenance.
• 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.
• 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.
• Debug API contracts, OAuth/login, tool invocation, latency, retries, rate limits, observability, data model, and user‑experience issues across partner and OpenAI systems.
• Review partner architectures and implementation plans for API design, scopes and permissions, data handling, safety, privacy, reliability, and long‑term maintainability.
• Contribute targeted fixes and improvements to ChatGPT, Codex, and the plugins platform, including APIs, SDKs, docs, examples, internal tooling, partner debugging workflows, and launch guardrails.
• Work with product, engineering, design, partnerships, legal, policy, support, and go‑to‑market teams to make partner launches smooth and repeatable.
• Bring structured signal from partners back to product and engineering, and turn patterns from successful launches into reusable playbooks, examples, platform requirements, and implementation guidance.

• Have 4-6 years of professional software engineering experience and are strong enough technically to contribute to the platform itself while still enjoying hands‑on coding.
• Have built and operated production APIs, backend services, developer platforms, apps, plugins, connectors, or integrations and can reason across frontend, backend, auth, reliability, privacy, evaluations, and UX constraints.
• Bring strong product sense and can distinguish a plugin that “works” from one that will be genuinely useful to users.
• Communicate clearly with external engineers, product leaders, executives, and internal cross‑functional stakeholders.
• Can make ambiguous partner ideas concrete through runnable prototypes, API contracts, technical specs, and pragmatic implementation guidance.
• Are comfortable reading unfamiliar code, making targeted platform changes, and debugging distributed systems with logs,…