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 @ 3
API @ 3
ChatGPT @ 3
Communication @ 3
Experimentation @ 2
Go @ 3
Node.js @ 3
Observability @ 3
Python @ 3
React @ 3
Security
TypeScript @ 3
- 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. It also addresses shared platform needs such as tool integration, permissions, quality measurement, and safe rollout. The team works closely with Design, Research, GTM, Security, platform teams, customers, and design partners.
This role is for a full-stack product engineer who can own ambiguous enterprise workflows end to end: understand customer problems, shape the product, build across frontend and backend, work through platform dependencies, instrument quality, and learn quickly with design partners.
Responsibilities
- Build and ship role-specific workflows across ChatGPT Work surfaces, services, plugins, and connectors.
- Turn customer and design-partner evidence into product decisions, milestones, and measurable quality gates without overfitting to a single customer.
- Partner with Design, Research, GTM, Security, and platform teams.
- Create robust evaluations, observability, and rollback paths.
- Own the full loop from prototype through bounded rollout and iteration.
- Define explicit contracts and fallback paths with shared platform teams when workflows depend on connectors, permissions, model routing, or other cross-team systems.
- Build across frontend, backend, APIs, data, and systems integrations.
- Work with data and permission boundaries when required by the experience.
- Make quality and rollout observable through evaluations, product and operational signals, and clear fallback or rollback paths.
Requirements
- Strong product engineering skills and excellent product judgment.
- Comfort moving across frontend, backend, APIs, data, and systems integration.
- Clear communication with customers and cross-functional partners.
- Ability to use evidence and tests to make ambiguous work observable.
- Attention to enterprise permissions, reliability, privacy, and rollout safety.
- Experience shipping user-facing products through ambiguity and explaining the related decisions, tradeoffs, and evidence.
- Ability to translate concrete customer workflows into general products without losing the details that make the first experience useful.
- Experience building and operating full-stack production products using a modern frontend stack such as React and TypeScript and backend services such as Python, Go, Node.js, or comparable technologies.
- Experience designing evolvable APIs, data models, and distributed or integration-heavy systems, including authentication, identity, permissions, secure data flows, and partial-failure behavior.
- Experience owning production systems at scale, including observability, performance, testing, incident response, safe migrations, staged rollout, and rollback.
- Experience building applied-AI or conversational products and evaluating probabilistic behavior with grounding, quality signals, and human-feedback loops.
- Experience building dashboards, data visualizations, or workflow and insight products that make complex information understandable and actionable.
- Familiarity with experimentation, product metrics, and iterative development, including instrumenting user outcomes from first use through retained usage.
Benefits
- Medical, dental, and vision insurance for employees and families, with employer contributions to Health Savings Accounts.
- Pre-tax accounts for health, dependent care, and commuter expenses.
- 401(k) retirement plan with employer match.
- Paid parental, medical, and caregiver leave.
- Paid time off, paid company holidays, office closures, and sick or safe time.
- Mental health and wellness support.
- Employer-paid basic life and disability coverage.
- Annual learning and development stipend.
- Daily meals in offices and eligible meal delivery credits.
- Relocation support for eligible employees.
- Potential additional taxable fringe benefits, including charitable donation matching and wellness stipends.
- OpenAI is an equal opportunity employer and provides reasonable accommodations to applicants with disabilities.