Senior Technical Program Manager, AI Infrastructure and Capacity Operations

• Own intake, triage, routing and request-quality standards for accelerator-capacity requests across multiple engineering and research teams.
• Run quarterly and annual demand forecasts, change control, review preparation, and follow-through; identify late, incomplete, or conflicting inputs early.
• Prepare capacity-planning and allocation reviews using demand, available supply, prior commitments, readiness, workload timing, and business priorities.
• Track capacity through its operational lifecycle—from request and forecast through delivery, readiness, assignment, and productive use.
• Coordinate infrastructure dependencies such as access, storage, data movement, networking, readiness checks, migration timing, and provider or provisioning tickets.
• Maintain dashboards and source-data quality, including freshness checks, ownership for missing inputs, reconciliation, and retirement of repeated manual reporting.
• Own operating cadences, agendas, action logs, dependency tracking, decision records, risk registers, blocking issue paths, and closure difficulty.
• Prepare concise leadership reporting that distinguishes facts, risks, decisions needed, options, recommended paths, accountable owners, and due dates.
• BS/MS/PhD in Electrical Engineering, Computer Science, Computer Engineering or similar (or equivalent experience).
• 7+ years of technical program management or closely related experience in AI/ML platforms, distributed systems, cloud infrastructure, compute capacity, or another technically demanding engineering environment.
• Shown ownership of recurring operational programs with scarce-resource trade-offs, multiple cadences, executive clarity, and overlapping peak periods.
• Strong program mechanics: intake compose, forecasting, review preparation, dependency management, decision and risk records, action closure, documentation, and status communication.
• Enough technical proficiency to understand infrastructure constraints, ask detailed questions, inspect requirements and metrics, and work credibly with engineers and researchers.
• Data proficiency sufficient to evaluate source quality, interpret dashboards, reconcile conflicting views, define useful operational measures, and identify missing ownership.
• Ability to influence without authority across research, platform engineering, infrastructure, data, finance, operations, and leadership collaborators!
• Experience with GPU or other accelerator-capacity planning, utilization programs, cluster operations, workload bring-up, or large-scale AI training and inference environments.
• Experience with demand and supply roadmaps, normalization across accelerator types, allocation reviews, quota or priority management, and capacity migrations.
• Familiarity with batch scheduling, cluster-management, cloud, or data-center environments and the operational dependencies that affect workload readiness.
• Experience with observability or dashboard platforms, data-quality controls, and automated reporting for infrastructure or service operations.
• Experience driving API-enabled workflow automation or decision-support tools with explicit human approval gates, audit evidence, and safe operating controls.
• You will also be eligible for equity and benefits .
• Applications for this job will be accepted at least until August 22, 2026.
• This posting is for an existing vacancy.
• NVIDIA uses AI tools in its recruiting processes.

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