Senior Technical Program Manager, AI Infrastructure and Capacity Operations
$168,000–$258,750 year
RemoteUnited States or Santa Clara, California, United States
Job Summary
Own intake, triage, and routing standards for accelerator-capacity requests across engineering and research teams. Run quarterly and annual demand forecasts, change control, and review preparation to identify late or conflicting inputs early. 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, and provisioning tickets. Maintain dashboards and source-data quality, including freshness checks, ownership for missing inputs, and retirement of repeated manual reporting. Own operating cadences, agendas, action logs, dependency tracking, decision records, risk registers, and blocking issue paths. Prepare concise leadership reporting that distinguishes facts, risks, decisions needed, options, recommended paths, accountable owners, and due dates.
Required Qualifications
- 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
- Consistent track record to transform ambiguous cross-functional work into a durable operating system with clear owners, decisions, and critical issue paths
- 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
Desired Qualifications
- 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
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