Technical Program Manager- AI Rack Scale Validation and Debug
Core
Lead end-to-end program planning and execution for GPU-based AI infrastructure, including server integration, rack bring-up, cluster-scale validation, and deployment readiness.
Role type
Senior Technical Program Manager (AI Infrastructure)
Builds
GPU platforms, rack-level solutions, and AI clusters for hyperscale and enterprise environments
Domain
AI Infrastructure / Datacenter Hardware / GPU Systems
Deliverable
production ML models
Required skills
Program planning and execution, Cross-functional coordination, Risk and dependency management, System debug and failure analysis, Incident response and escalation, Operational metrics tracking (MTTD/MTTM/MTTR), AI-driven workflow automation (Agentic AI/AIOps), Technical understanding of GPU/server/rack architectures, Stakeholder communication
Preferred skills
Hardware/systems engineering background, GPU cluster scale testing experience, Rack-level bring-up expertise, Fleet-scale validation experience, Infrastructure observability knowledge, PMP/Scrum certification
Technologies
Jira, Confluence, Excel, PowerPoint
Responsibilities
Lead end-to-end program planning and execution for GPU-based AI infrastructure, Coordinate multi-node and multi-rack scale testing, Drive rack-level solution execution across compute/switch trays and infrastructure, Lead coordination of platform and rack-level debug activities, Track high-impact GPU/firmware/rack/networking failures, Establish and track operational metrics for fleet health, Identify opportunities to apply Agentic AI and AIOps to engineering workflows, Provide clear, data-driven program updates to engineering teams and senior leadership
