Description
Compensation
The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The salary range for this position is $257K – $445K, with generous equity, performance-related bonuses for eligible employees, and the following benefits:
- Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
- Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
- 401(k) retirement plan with employer match
- Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
- Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
- 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
- Mental health and wellness support
- Employer-paid basic life and disability coverage
- Annual learning and development stipend to fuel your professional growth
- Daily meals in our offices, and meal delivery credits as eligible
- Relocation support for eligible employees
- Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.
About the Team
The Product & Platform teams at OpenAI are responsible for delivering the company’s most impactful offerings,such as ChatGPT, our API platform, and new enterprise capabilities,to a global and diverse customer base. The ChatGPT infrastructure team is responsible for ensuring that our products can serve rapidly growing demand with the performance, reliability, and quality our users expect.
About the Role
We are seeking a Technical Program Manager to lead the operating system for Chat capacity and model deployment. You will connect demand forecasting and capacity allocation with model readiness, rollout planning, launch coordination, and post-deployment learning. You will also own model deployment beyond capacity by working with cross-functional teams across research, post-training, inference, and product to own mainline model deployment.
Responsibilities
- Own cross-functional programs for Chat capacity forecasting, allocation, headroom planning, and constrained-capacity operations.
- Build durable intake, prioritization, and decision mechanisms that connect 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 timely allocation decisions.
- Lead model deployment readiness and rollout planning, including serving-capacity allocation, launch sequencing, validation, and operational handoffs.
- Establish clear readiness gates, risk reviews, rollback criteria, and escalation paths for model deployments.
- Drive launch coordination 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 make dependencies, risks, capacity constraints, and launch choices clear to technical and product leaders.
Requirements
- Have led complex technical programs in infrastructure, distributed systems, capacity planning, model serving, or large-scale deployment environments.
- Can reason credibly about demand, supply, headroom, reliability, latency, and quality tradeoffs, and translate them into executable plans.
- Have built operating mechanisms or tooling that replaced fragmented, manual workflows with scalable systems and clear ownership.
- Are effective in high-ambiguity, constrained environments where priorities change and decisions require explicit tradeoffs.
- Build alignment across research, engineering, product, finance or capacity planning, and operations without relying on direct authority.
- Use metrics to guide decisions, identify bottlenecks, and demonstrate measurable improvements in throughput, predictability, or reliability.
- Communicate with precision and can move comfortably between technical detail, operational execution, and executive-level decisions.
- Thrive in ambiguous, scaling environments and can bring order to complex cross-functional work without losing pace.
- Care about OpenAI's mission and about expanding responsible access to advanced AI systems.