Snowflake is seeking a Technical Program Manager for Compute Infrastructure to own and run programs that bring AI compute capacity online, partnering with infrastructure engineering, product, and finance teams to turn AI workload needs into prioritized capacity plans. The role will help shape how Snowflake scales its AI compute, directly affecting how quickly Snowflake ships AI capabilities to customers.
Responsibilities
Own and run programs that bring AI compute capacity online, from demand intake through procurement, deployment, and handoff to engineering teams; Partner with infrastructure engineering, product, and finance teams to turn AI workload needs into clear, prioritized capacity plans; Build and improve demand planning processes, including intake standards, forecasting inputs, and regular planning cycles; Track compute utilization and efficiency, surface trends early, and bring clear, data-informed recommendations to stakeholders; Identify risks and dependencies across hardware supply, cloud providers, and internal teams, and drive them to resolution before they slow delivery; Communicate program status, trade-offs, and decisions clearly to engineering partners and leadership; Use AI-assisted workflows and automation to reduce manual coordination and make planning faster and more accurate
Requirements
2+ years of experience in technical program management, engineering, or a related technical role, preferred; Experience delivering cross-functional programs in cloud infrastructure, distributed systems, or large-scale compute environments; A working understanding of how compute capacity is planned and consumed, such as GPUs, accelerators, or cloud instances; Strong analytical skills and comfort using data to frame problems, weigh trade-offs, and guide decisions; Clear written and verbal communication, with the ability to align technical and non-technical stakeholders; The ability to bring structure to ambiguous problems and keep work moving in a fast-paced environment; A BS in Computer Science, Engineering, or a related technical field, or equivalent experience
Nice to have
Experience with GPU capacity planning, quota management, or AI/ML infrastructure programs; Familiarity with major cloud providers (AWS, Azure, GCP) and how they supply and price compute; Exposure to ML model serving, training, or inference workloads and what drives their resource needs; Hands-on use of AI tools and agents, such as Snowflake Cortex AI, to automate planning, reporting, or coordination; Experience designing incentive or governance models that improve resource efficiency across teams