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Technical Program Manager, AI Infrastructure Capacity Planning

OpenAI

San FranciscoFull TimeSenior
Sign in to applyVerified 2h ago
Location
San Francisco
Employment
Full Time
Work model
On-Site
Level
Senior
Posted
2h ago

Skills

PythonSQL

About this role

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. This is not a finance-only forecasting or reporting role. Success requires technical fluency across the infrastructure stack, strong analytical judgment, and the ability to move consequential decisions forward when requirements, timelines, and supply conditions change quickly.

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

Listing verified 2h ago. Applications go through the company's official careers site.

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