Technical Program Manager, Compute Infrastructure

OpenAI • San Francisco, CA

8d • Hybrid

About The Position

The compute infrastructure team runs the GPU fleet and large-scale compute clusters that serve the models backing ChatGPT and the API, while also supporting training workloads for our next generation models. We operate a large, modern GPU fleet and provide a unified platform for other OpenAI teams to seamlessly run production Applied AI and Research training workloads.
We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth.
You will be part of an engineer-first TPM team as a Technical Program Manager for Compute Infrastructure who owns the end-to-end delivery of large-scale GPU clusters, partnering with engineers to bring clusters online across external providers and partners. You’ll run a broad, parallel portfolio spanning hardware, networking, power, and cooling—driving execution, risk management, and crisp alignment from working teams through leadership to deliver production-ready capacity at scale.
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

Requirements

• Possess a degree in a hard science, or have a demonstrated track record of engineering expertise.
• Have 5+ years of experience in program management for major projects including capital projects or hyperscaler infrastructure deployment.
• Demonstrate the ability to serve as the go-to person solely responsible for driving and delivering complex projects.
• Are comfortable managing cross-functional and cross-company teams; experience driving information and decision hygiene.
• Have an extensive track record of successfully delivering high-profile, technical projects against tight deadlines.
• Are technically adept and have effectively partnered with engineering or fundamental research teams of the highest caliber.
• Have experience interfacing with and leading external vendors including engineering firms, equipment suppliers, and/or construction firms.
• Have expertise in designing and implementing simple, scalable processes that solve complex problems.
• Have experience managing complicated dependencies such as logistics and/or supply chains.
• Are relentlessly resourceful and thrive in ambiguous, fast-paced environments.
• Are interested in and thoughtful about the impacts of AGI.

Responsibilities

• Lead end-to-end delivery of both New Compute SKUs and large-scale GPU clusters across an external partner ecosystem while supporting capacity planning for training and inference.
• Ability to contextually drive multi-threaded bring-up programs spanning hardware, networking, power, and cooling—owning plans, dependencies, and critical paths.
• Interface with chip providers to derisk long-term onboarding to new hardware platforms by working across kernels, comms, hardware, and scheduling engineering teams.
• Build and operationalize program mechanisms (roadmaps, milestones, risk registers, runbooks) that make delivery predictable at massive scale.
• Partner with engineering to improve cluster turn-up reliability, repeatability, and automation, reducing time-to-serve for new capacity.
• Coordinate cross-functional readiness (security, finance, operations, product/research stakeholders) to ship production-ready compute.
• Manage integration and handoffs across teams and partners—ensuring consistent execution, clear communication, and fast issue resolution.
• Identify bottlenecks and systemic gaps, then drive durable fixes across tooling, process, and partner interfaces.
• Provide crisp executive visibility on progress, tradeoffs, and risks across a large portfolio of concurrent programs.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed