Technical Program Manager, Research Compute Services

The role

You will build and own the tools, data, and platform that turn Research plans and workload signals into concrete compute demand and manage allocations across the fleet. This is a hands-on technical role working directly with code and data to prototype solutions and automate workflows.

What you will do

• Work directly with researchers to translate needs into improvements across compute services, tooling, and scheduling.
• Own the roadmap and delivery of tools, data, and platforms used to capture and manage research demand and allocations.
• Develop systems that translate research plans into concrete capacity needs.
• Partner with Capacity Planning, Research, and infrastructure teams to reconcile demand with available supply.
• Create data models, views, and automation to show researcher needs and capacity usage.
• Partner with engineers working on Kubernetes deployments and scheduling systems.
• Work with engineers to evaluate optimization approaches for fleet and local scheduling.
• Use workload and fleet data to identify bottlenecks and unused capacity.
• Lead technical delivery across Research, Research Compute Services, Capacity Planning, and infrastructure engineering.
• Provide clear views of demand, allocation constraints, and delivery progress to teams and leadership.

Required qualifications

• Strong engineering foundation developed through relevant education or demonstrated technical experience.
• Led and delivered complex technical programs involving large-scale compute, distributed systems, infrastructure platforms, or research environments.
• Practical experience with capacity planning, including supply and demand management, compute allocations, and supporting tools and data.
• Personally built or materially contributed to tools, data systems, or automation used by engineering or research teams.
• Comfortable working directly with code and operational data.
• Familiar with Kubernetes deployments and scheduling systems.
• Understand how resource constraints and placement decisions affect workload execution.
• Understand optimization solvers and can reason about their use in fleet-wide allocation and local scheduling.
• Can take ownership of ambiguous technical problems and establish a clear path forward.
• Communicate technical decisions, constraints, and priorities clearly across engineering, Research, and leadership.
• Resourceful and comfortable with changing priorities.
• Interested in and thoughtful about the impacts of AGI.

About the company

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. They push the boundaries of AI capabilities and seek to safely deploy them to the world through their products.