Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 4
API @ 7
ChatGPT @ 4
Distributed Systems @ 4
Go @ 4
Mentoring @ 7
Node.js @ 4
Observability @ 4
People Management @ 6
Python @ 4
React @ 4
Security @ 4
TypeScript @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Enterprise Verticals builds role-specific ChatGPT Work experiences for high-value enterprise workflows. The team combines product engineering, plugins and skills, connectors, data, evaluations, and customer evidence to turn useful demos into reliable daily work.
The Technology vertical focuses on repeatable workflows for people at technology companies, including data and analytics, sales, and design. The team also addresses shared platform needs such as tool integration, permissions, quality measurement, and safe rollout.
The role involves defining and building AI-powered enterprise workflows, translating customer needs into product direction, designing the underlying systems, and writing and shipping production-quality code across the stack. The engineer will own technical direction and end-to-end delivery across ChatGPT Work surfaces, backend services, plugins, connectors, enterprise data, permissions, and evaluations.
This is an individual-contributor role focused on technical judgment, direct execution, and influence rather than people management.
Responsibilities
- Set the technical direction for role-specific enterprise AI experiences and personally design, build, and ship critical components across ChatGPT Work surfaces, services, plugins, and connectors.
- Translate ambiguous customer and design-partner needs into product and technical strategies with 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 implementation.
- Architect production-grade systems and establish evaluation, instrumentation, security, reliability, staged-rollout, and rollback standards for probabilistic AI experiences.
- Own the complete product and engineering lifecycle, including 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.
Requirements
- Deep experience as a hands-on product engineer, typically with 10+ years building production software.
- Ability to independently architect and implement sophisticated systems across frontend, backend, APIs, data, distributed services, and complex enterprise integrations.
- Ability to earn customer trust, influence senior stakeholders, and guide cross-functional teams toward decisions without relying on formal authority.
- Experience turning uncertainty into disciplined execution plans using experiments, evaluations, instrumentation, and customer evidence.
- Strong understanding of enterprise identity, permissions, privacy, security, performance, reliability, and operational readiness.
- Repeated experience leading the architecture and hands-on delivery of important user-facing products from ambiguous beginnings through production use.
- Extensive experience personally building and operating full-stack production products.
- Modern frontend experience with React and TypeScript.
- Backend experience with Python, Go, Node.js, or comparable languages.
- Experience setting technical direction for complex, integration-heavy, or distributed systems.
- Deep understanding of APIs, data models, enterprise identity, authorization, secure data flows, and partial-failure behavior.
- Experience owning 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, including understanding of model behavior, tool use, grounding, evaluations, human feedback, and reliability challenges in probabilistic systems.
- Experience designing and building workflow, data, analytics, visualization, or insight products for 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.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. OpenAI is an equal opportunity employer and does not discriminate on the basis of legally protected characteristics. Background checks are administered in accordance with applicable law. Reasonable accommodations are available to applicants with disabilities.