Technical Program Manager, AI Cluster Validation

What you'll do

• Drive end-to-end execution of AI cluster engineering programs including GPU platforms and rack-level solutions.
• Manage program artifacts such as schedules, dependency maps, resource forecasts, and risk logs.
• Coordinate across hardware, firmware, and networking teams to ensure readiness for scale testing and customer workloads.
• Lead the delivery of multi-node and multi-rack scale testing including test strategy and coverage tracking.
• Oversee rack bring-up processes involving compute trays, cabling, power, cooling, and management infrastructure.
• Act as the execution lead for platform debug to coordinate triage and root-cause analysis for system-level issues.
• Track high-impact failures across GPU, firmware, and network components to ensure timely resolution.
• Provide data-driven status reports and risk assessments to senior leadership.

What we're looking for

• Bachelor's or master's degree in systems, EE, CS, or a related engineering discipline.
• Experience leading complex hardware or AI infrastructure programs through bring-up, validation, and deployment phases.
• Strong technical understanding of GPU-based AI systems, rack architectures, and datacenter infrastructure.
• Proven ability to manage ambiguity, drive debug execution, and lead cross-functional teams without direct authority.
• Strong written and verbal communication skills for executive-level status reporting.
• Proficiency with program management tools such as Jira, Confluence, and Excel/PowerPoint.
• Hands-on experience with GPU cluster scale testing, system stress, or performance validation (preferred).
• Familiarity with rack-level bring-up, power/cooling constraints, networking, and failure modes at scale (preferred).