GPT Infrastructure Lead

About the Team OpenAI’s Industrial Compute team is responsible for building and scaling large-scale compute capacity across first-party data centers, strategic partners, and industrial infrastructure environments. We focus on converting power, land, hardware, and operational execution into reliable compute capacity that can support frontier AI training and inference workloads. This team operates at the intersection of infrastructure delivery, hardware systems, utilities, supply chain, and capacity strategy—ensuring OpenAI can scale compute faster than traditional models allow. About the Role We are seeking a GPT Infrastructure Lead to drive the end-to-end conversion of industrial-scale infrastructure investments into usable token capacity for OpenAI workloads. In this role, you will own execution across complex compute programs where raw infrastructure capacity must be transformed into operational GPU throughput. You will coordinate across data center delivery, power, networking, hardware deployment, workload enablement, finance, and external partners to ensure capacity becomes productive tokens as quickly and efficiently as possible. This role is ideal for someone who can bridge physical infrastructure delivery with compute utilization outcomes. Success requires strong systems thinking, elite program leadership, and the ability to drive accountability across internal teams and strategic partners. In this role, you will - Lead GPT Infrastructure programs across industrial compute environments, including first-party and partner-owned capacity. - Convert delivered power, space, and hardware capacity into production-ready token throughput. - Build integrated execution plans spanning construction, power energization, rack deployment, networking, cluster readiness, and workload onboarding. - Partner with infrastructure engineering, hardware, networking, finance, supply chain, and operations teams. - Drive external providers, EPCs, OEMs, utilities, and strategic partners

Department: Scaling; Team: Hardware