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
ChatGPT
Communication @ 3
Distributed Systems @ 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
The Product & Platform teams deliver OpenAI's products, including ChatGPT, the API platform, and enterprise capabilities, to a global customer base. The ChatGPT infrastructure team ensures that these products serve growing demand with the expected performance, reliability, and quality.
This role operates at the intersection of product demand, model deployment, inference, research, fleet, and capacity. It connects demand forecasting and capacity allocation with model readiness, rollout planning, launch coordination, and post-deployment learning.
Responsibilities
- Own cross-functional programs for Chat capacity forecasting, allocation, headroom planning, and constrained-capacity operations.
- Build durable intake, prioritization, and decision mechanisms connecting product demand and model requirements to available serving capacity.
- Partner with product, research, inference, fleet, and capacity teams to develop scenarios, surface tradeoffs, and drive allocation decisions.
- Lead model deployment readiness and rollout planning, including serving-capacity allocation, launch sequencing, validation, and operational handoffs.
- Establish readiness gates, risk reviews, rollback criteria, and escalation paths for model deployments.
- Coordinate launches through deployment and post-launch learning, turning recurring gaps and manual work into scalable tooling and operating practices.
- Define and operationalize metrics for forecast accuracy, capacity utilization and headroom, deployment velocity, reliability, latency, quality, and user impact.
- Create concise, decision-ready communications that clarify dependencies, risks, capacity constraints, and launch choices for technical and product leaders.
Requirements
- Experience leading complex technical programs in infrastructure, distributed systems, capacity planning, model serving, or large-scale deployment environments.
- Ability to reason about demand, supply, headroom, reliability, latency, and quality tradeoffs and translate them into executable plans.
- Experience building operating mechanisms or tooling that replace fragmented, manual workflows with scalable systems and clear ownership.
- Ability to operate effectively in high-ambiguity, constrained environments where priorities change and decisions require explicit tradeoffs.
- Ability to build alignment across research, engineering, product, finance or capacity planning, and operations without relying on direct authority.
- Experience using metrics to guide decisions, identify bottlenecks, and demonstrate improvements in throughput, predictability, or reliability.
- Precise communication skills, with the ability to move between technical detail, operational execution, and executive-level decisions.
- Ability to bring structure to complex cross-functional work in scaling environments.
- Commitment to OpenAI's mission and to expanding responsible access to advanced AI systems.
Work Arrangement
- Based in San Francisco, California.
- Hybrid work model with three days in the office per week.
Benefits
- Equity, performance-related bonuses for eligible employees, and a base salary range of $257,000–$445,000 per year.
- Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
- Pre-tax accounts for health and dependent care expenses, parking, and transit.
- 401(k) retirement plan with employer match.
- Paid parental, medical, and caregiver leave.
- Paid time off, paid company holidays, office closures, and paid sick or safe time as required by law.
- Mental health and wellness support.
- Employer-paid basic life and disability coverage.
- Annual learning and development stipend.
- Daily office meals and eligible meal delivery credits.
- Relocation support for eligible employees.
- Additional taxable fringe benefits may include charitable donation matching and wellness stipends.
OpenAI is an equal opportunity employer committed to reasonable accommodations and responsible development and deployment of artificial intelligence.
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