The opportunity
Enterprise Verticals builds role-specific ChatGPT Work experiences for high-value enterprise workflows. We combine product engineering, plugins and skills, connectors, data, evaluations, and customer evidence to turn useful demos into reliable daily work.
What you'll do
Set the technical direction for role-specific enterprise AI experiences, and: personally design, build, and ship their most critical components across ChatGPT Work surfaces, services, plugins, and connectors.
Turn ambiguous customer and design-partner needs into a clear, generalizable: product and technical strategy, with explicit milestones, architectural decisions, and measurable quality and adoption goals.
Lead complex initiatives across Design, Research, GTM, Security, and platform: teams; align senior stakeholders; make consequential tradeoffs; and drive decisions through to implementation.
Architect production-grade systems and establish the evaluation,: instrumentation, security, reliability, staged-rollout, and rollback standards required to operate probabilistic AI experiences safely.
Own the complete product and engineering lifecycle: problem definition, technical design, hands-on prototyping, production implementation, launch, customer feedback, and sustained iteration.
Define durable technical contracts and fallback strategies across connectors,: identity, permissions, enterprise data, model routing, and shared platform dependencies; raise the engineering bar through architecture reviews, mentorship, and reusable patterns.
What they're looking for
- Extensive experience personally building and operating full-stack production: products, including modern frontend technologies such as React and TypeScript and backend services in Python, Go, Node.js, or comparable languages.
- A track record of setting technical direction for complex, integration-heavy: or distributed systems, with deep understanding of APIs, data models, enterprise identity, authorization, secure data flows, and partial-failure behavior.
- Demonstrated ownership of business-critical production systems at scale,: including architecture, performance, observability, testing, incident response, migrations, staged delivery, and operational excellence.
- Experience shipping applied AI, agentic, or conversational products, with a: practical understanding of model behavior, tool use, grounding, evaluations, human feedback, and the reliability challenges of probabilistic systems.
- Experience designing and building sophisticated workflow, data, analytics,: visualization, or insight products that make complex systems genuinely useful to enterprise users.
- A strong record of leading through technical judgment, mentoring experienced: engineers, shaping cross-team architecture, and connecting engineering decisions to measurable customer outcomes and sustained adoption.
