Technical Program Manager, Capacity Analytics & Tooling

OpenAI•San Francisco, CA

7h•$207,000 - $285,000•Hybrid

About The Position

Join OpenAI’s Compute Infrastructure TPM team as the Technical Program Manager for Capacity Analytics & Tooling. You will serve as product manager for supply and demand planning tools, owning their strategy, roadmap, and delivery. The tools help teams forecast demand, understand supply, and plan allocations. Users and partners include Product TPMs, Capacity TPMs, Compute TPMs, Finance, Accounting, Leadership, Engineering, and Research. The role combines product management, technical program leadership, data engineering, and applied data science. You will partner with engineering and data teams to build reliable data foundations, improve forecasting and scenario planning, and scale tools and success metrics across CPU, storage, network, and GPU resources. You will help teams make informed capacity decisions across AWS, GCP, Azure, OCI, and other infrastructure providers. The position is based in San Francisco, California, with a hybrid work model requiring three days per week in the office. Relocation assistance is offered to new employees.

Requirements

At least 5 years of experience leading technical programs or products in data platforms, infrastructure, capacity planning, or a related field, with a record of delivering systems teams rely on.
Experience owning an internal product or platform roadmap and translating complex operational needs into requirements, priorities, and releases that users adopt.
Direct capacity-planning experience, including demand forecasting, supply planning, allocations, and resource constraints; understanding of how utilization, performance, availability, and cost affect planning decisions.
Understanding of modern data infrastructure, including ingestion, transformation, batch and streaming processing, and analytical storage; experience with technologies such as Fivetran, dbt, Spark, Kafka, or comparable systems and ability to discuss architectural tradeoffs.
Practical experience with data modeling, data cleaning, validation, and reconciliation; ability to use SQL and Python or similar tools to investigate discrepancies, validate assumptions, and prototype analyses.
Experience applying quantitative methods to forecasting, scenario analysis, or optimization, including assessing model assumptions and uncertainty, evaluating forecast performance, and explaining analytical limitations.
Understanding of capacity, performance, and cost characteristics of compute, storage, networking, and accelerators, with experience across multiple cloud environments.
Ability to lead complex programs with technical dependencies, align teams with different priorities, and clearly communicate technical tradeoffs to engineers, researchers, finance partners, and leaders.
Resourcefulness in ambiguous environments, sound product judgment, and ability to build simple, scalable solutions to complex planning problems.
Interest in and thoughtful consideration of the impacts of AGI.

Responsibilities

Own the product strategy and roadmap for supply and demand planning tools, setting priorities and success measures and guiding delivery from requirements through adoption and improvement.
Build planning workflows for demand intake, forecasting, supply tracking, scenario analysis, and allocation planning.
Partner with engineering to scale the data infrastructure used for capacity planning, guiding ingestion, transformation, storage, and delivery decisions.
Establish shared data models and definitions for supply, demand, allocations, utilization, and cost; drive data cleaning, validation, reconciliation, and traceability.
Improve forecasting and analytical capabilities by connecting product and research plans to infrastructure demand and making assumptions, uncertainty, forecast accuracy, and capacity constraints visible.
Define and scale metrics for data quality, forecast performance, planning speed, tool adoption, capacity availability, utilization, and efficiency across CPU, storage, network, and GPU resources.
Support planning across AWS, GCP, Azure, OCI, and other providers, accounting for differences in resource types, regions, availability, commercial commitments, and deployment constraints.
Lead delivery across data, infrastructure, and planning teams, managing dependencies, technical tradeoffs, migrations, risks, and releases.
Drive adoption through workflows, documentation, training, and feedback mechanisms; identify manual reconciliation and reporting work that can be improved with better data and automation.
Make capacity tradeoffs clear to leadership and partner teams by presenting supply-demand gaps, allocation options, and financial and operational consequences.
Partner with Finance and Accounting to align planning data with budgeting and reporting needs.