OpenAI

Token-as-a-Service Technical Program Manager

OpenAI$130K — $180K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 8+ years of Technical Program or Engineering Program Management experience
  • Experience in large-scale technical programs with cloud and hardware systems
  • Strong understanding of compute infrastructure, networking, and production systems
  • Proven cross-functional execution skills across various departments
  • Ability to manage executive stakeholders and communicate complex tradeoffs
  • Strong analytical skills for assessing metrics like throughput and capacity
  • Experience with external providers or hyperscalers is a plus

Responsibilities

  • Lead delivery programs converting external infrastructure into production-ready token supply
  • Ensure readiness of compute, storage, networking, and security for third-party environments
  • Build integrated plans with clear milestones and risk assessments
  • Drive execution for launching new partner regions and expansions
  • Measure deployed capacity against usable token output with operating mechanisms
  • Identify and address bottlenecks in token generation processes
  • Manage escalations during high-severity delivery issues

Benefits

  • Hybrid work model with 3 days in-office per week
  • Relocation assistance available
  • High-visibility role with direct impact on scaling global model training
  • Opportunity to work at the intersection of tech execution and business objectives
  • Potential for career growth in a fast-scaling environment
Full Job Description
About the Role

We are seeking a Technical Program Manager, Token-as-a-Service (TaaS) to lead delivery of external compute capacity that directly serves OpenAI model workloads.

In this role, you will own complex cross-functional programs that transform third-party infrastructure into usable tokens at scale. You will partner across engineering, capacity planning, networking, hardware, finance, product, and external providers to ensure that deployed capacity translates into real production throughput.

This role sits at the intersection of infrastructure execution, systems readiness, and business impact. Success requires strong technical fluency, elite program management, and the ability to drive accountability across internal teams and external partners.

This is a high-visibility role with direct impact on OpenAI's ability to scale model training and inference globally.

This role is based in San Francisco, CA, with a hybrid work model of 3 days in office per week. Relocation assistance is available.

Key Responsibilities
  • Lead end-to-end delivery programs that convert external infrastructure capacity into production-ready token supply.
  • Own readiness across compute, storage, networking, security, and operational dependencies for third-party environments.
  • Build integrated plans across internal engineering teams and external partners with clear milestones, owners, risks, and critical paths.
  • Drive launch execution for new partner regions, clusters, and capacity expansions.
  • Create operating mechanisms that measure deployed capacity versus usable token output.
  • Identify bottlenecks preventing token generation (network constraints, hardware readiness, software enablement, partner delays, etc.) and drive resolution.
  • Coordinate with capacity planning and finance teams to prioritize the highest ROI capacity opportunities.
  • Establish executive-level reporting on delivery status, risks, and token ramp forecasts.
  • Improve repeatability of partner onboarding, technical integration, and scaling motions.
  • Manage escalations across internal and external stakeholders during high-severity delivery issues.
  • Translate ambiguous infrastructure constraints into clear execution plans.
  • Help define the long-term operating model for Token-as-a-Service across Stargate and 3P ecosystems.


Qualifications
  • 8+ years of Technical Program Management, Engineering Program Management, or Infrastructure Delivery experience.
  • Experience leading large-scale technical programs involving cloud, data center, networking, hardware, or distributed systems.
  • Strong understanding of compute infrastructure, clusters, networking, storage, and production systems.
  • Proven ability to drive cross-functional execution across engineering, operations, finance, and external vendors.
  • Experience managing executive stakeholders and communicating complex tradeoffs clearly.
  • Strong analytical skills with ability to reason about utilization, throughput, capacity, and operational metrics.
  • Comfortable operating in ambiguous, fast-scaling environments.
  • Strong written and verbal communication skills.
  • High ownership mentality with bias toward action.
  • Experience working with external providers, strategic partners, or hyperscalers is highly preferred.


Preferred Skills
  • Experience with GPU clusters, AI infrastructure, or large-scale model serving environments.
  • Familiarity with token economics, inference capacity planning, or workload scheduling.
  • Experience scaling global infrastructure through third-party providers.
  • Background in systems engineering, networking, or hardware deployment programs.
  • Experience building new operational models in high-growth environments.

About OpenAI

OpenAI is an artificial intelligence research laboratory consisting of the for-profit corporation OpenAI LP and its parent company, the non-profit OpenAI Inc. The company was founded in 2015 by a group of technology leaders, including Elon Musk, Sam Altman, Greg Brockman, Ilya Sutskever, and John Schulman. OpenAI's mission is to develop and promote friendly AI for the betterment of humanity. The company has developed a number of cutting-edge AI technologies, including GPT-3, a language processing system that can generate human-like text. OpenAI has received funding from a number of high-profile investors, including LinkedIn co-founder Reid Hoffman and venture capitalist Peter Thiel.
Learn more about OpenAI
Size
100 employees
Industry
Founded
2015

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