AI Deployment Engineer, Ecosystem

Responsibilities

• 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.

Requirements

• 4-6 years of professional software engineering experience and strong enough technically to contribute to the platform itself while still enjoying hands-on coding.
• 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.
• 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.
• Comfortable reading unfamiliar code, making targeted platform changes, and debugging distributed systems with logs, traces, metrics, and experiments.
• Care deeply about user trust, privacy, data handling, and product quality in AI-powered experiences.
• Balance urgency with judgment and can keep launches moving while staying precise about details that matter.

Nice-to-Haves

• 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, including leading technical calls, navigating ambiguity, and helping external teams ship production software.
• 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 when needed.
• Strong written communication skills, including docs, implementation notes, launch plans, and partner-facing technical guidance.