Description
Compensation
- $257K – $335K • Offers Equity
The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) 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
OpenAI's Industrial Compute organization builds and operates the infrastructure required to train and serve frontier AI models. The Capacity Planning team connects rapidly changing research and product demand with the compute, networking, storage, power, data center, hardware, and operational resources required to make that demand executable.
About the Role
We are seeking a Technical Program Manager to build and lead capacity planning across OpenAI's large-scale AI infrastructure. You will translate uncertain workload demand into clear infrastructure requirements, allocation decisions, supply commitments, activation priorities, and long-range capacity strategies.
This role sits at the intersection of research, engineering, infrastructure, finance, sourcing, deployment, and operations. You will create the planning models, operating cadences, governance mechanisms, and source-of-truth systems that allow teams to understand what capacity is required, what is available, what is at risk, and what decisions must be made.
Key Responsibilities
- Own capacity-planning processes across near-term workload allocation, quarterly execution, and longer-range infrastructure horizons.
- Translate research, training, inference, and product demand into compute, accelerator, cluster, networking, storage, rack, power, and site requirements.
- Develop scenarios that make assumptions, confidence levels, constraints, sensitivities, and decision points explicit.
- Reconcile requested demand against contracted, delivered, installed, activated, and workload-usable capacity.
- Partner with research and engineering teams to understand workload priorities, technical dependencies, utilization patterns, and changing requirements.
- Partner with sourcing, finance, hardware, deployment, and operations teams to align supply commitments, activation schedules, costs, and delivery risks.
- Support allocation and prioritization decisions when infrastructure is constrained or delivery plans change.
- Track infrastructure lead times, critical dependencies, utilization, headroom, forecast accuracy, activation readiness, and capacity risk.
- Build dashboards, analytical tools, executive updates, and operating cadences that create a credible source of truth.
- Drive mitigation plans for site delays, hardware shortages, network or storage constraints, workload changes, and other capacity risks.
- Continuously improve planning models, governance, data quality, and accountability as OpenAI's infrastructure scales.
Qualifications
- 8+ years of experience in technical program management, infrastructure capacity planning, cloud infrastructure, supply planning, or a closely related field.
- Demonstrated ownership of capacity planning for large-scale distributed systems, cloud platforms, AI or ML workloads, or hyperscale infrastructure.
- Ability to translate ambiguous demand into structured assumptions, scenarios, technical resource requirements, and executable plans.
- Technical fluency across compute, networking, storage, data center infrastructure, utilization, reliability, and deployment dependencies.
- Strong analytical skills and experience developing planning models, operational metrics, dashboards, or data-driven decision systems.
- Experience leading decisions across engineering, finance, sourcing, deployment, operations, and executive stakeholders.
- Excellent written and verbal communication, including the ability to explain uncertainty, tradeoffs, and recommendations clearly.
Preferred Skills
- Experience planning GPU, accelerator, or AI infrastructure capacity for training or inference workloads.
- Experience with cluster allocation, cloud capacity, hardware supply, infrastructure procurement, site readiness, or production activation.
- Familiarity with forecasting methods, scenario planning, optimization, cost attribution, capacity economics, and utilization management.
- Experience building planning tools or source-of-truth systems using SQL, Python, spreadsheets, BI platforms, or similar technologies.
- Track record of improving utilization, reducing infrastructure cost or risk, and enabling critical workloads during periods of constrained supply.