Senior Technical Program Manager, AI Infrastructure and Capacity Operations

NVIDIA•Us, CA

About The Position

We are seeking a Technical Program Manager to lead recurring capacity operations for large-scale AI infrastructure programs and support tooling and automation initiatives! You will build the mechanisms that keep demand, supply, readiness, risks, decisions, and delivery work visible, sequenced, detailed, and moving. This is an operational leadership role, not a meeting-coordination role. You will challenge incomplete inputs, establish operating cadences, turn ambiguous constraints into clear decisions, and close cross-functional actions - partnering with, not replacing, technical owners.

Requirements

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 record keeping, 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.
Consistent track record to transform ambiguous cross-functional work into a durable operating system with clear owners, decisions, and critical issue paths with excellent written and verbal communication, including the ability to turn sophisticated updates into concise decisions, risks, options, actions, and leadership mentorship.
Ability to influence without authority across research, platform engineering, infrastructure, data, finance, operations, and leadership collaborators!

Nice To Haves

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.

Responsibilities

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.