AI Cluster Technical Program Manager – Validation, Debug & Agentic AI

ADVANCE YOUR CAREER. ADVANCE THE WORLD. At AMD, we believe technology can change lives for the better. It can heal us, entertain us, and make us more connected, productive, and understanding of the world around us. And we’re looking for talent who feel the same: people who want to leave the planet better than they found it, those who don’t shy away from humanity’s challenges but are determined to help solve them.   AMD is powering the next generation of supercomputing, high-performance computing, cloud, and AI. Whether you’re designing next-gen processors, enabling AI breakthroughs, or creating go-to-market plans, every role at AMD contributes to something bigger — technology that moves the world forward.

We are seeking a Technical Program Manager to lead execution of AI cluster engineering programs with deep focus on GPU platforms, rack-level solutions, and AI Cluster validation. This role is responsible for driving end-to-end delivery from GPU + server integration through rack bring-up, scale testing, failure analysis, and system debug closure, ensuring platform readiness for hyperscale and enterprise AI deployments.   This role operates at the intersection of hardware, firmware, networking, and scale-test execution, and requires strong technical depth combined with disciplined program execution.     THE PERSON: You are a hands-on TPM who thrives in complex, fast-moving ecosystems, and can connect deep technical details to crisp program plans, executive reporting, and customer outcomes. You are comfortable driving execution in bring-up and EVT/DVT/PVT working closely with engineers to root-cause issues, unblock debug, and make data-driven tradeoffs to keep programs moving. You bring urgency, ownership, and clarity to ambiguous problem spaces and can communicate effectively from lab floor to executive review.

Program Leadership & Execution   Define, plan, and drive program plans for AI infrastructure systems validation and readiness, including server integration, rack bring-up, and cluster-scale deployment readiness.    Create and maintain core PM artifacts: schedules, dependency maps, resource forecasts, risk/issue logs, and program dashboards/status reports.    Identify and drive mitigation plans for issues/risks, including cross-team escalations and corrective actions across multiple engineering areas.    Drive regular execution reviews with engineering teams and provide concise, data-driven updates to senior leadership.     GPU & Platform Execution   Own program execution for GPU-based AI platforms, spanning system bring-up, qualification, scale readiness, and deployment validation across server, rack, and cluster levels.   Drive alignment across GPU, CPU, firmware, BIOS/BMC, and system teams to ensure readiness for scale testing and customer workloads.   Track platform issues, and debug dependencies; ensure risks are clearly documented, owned, and mitigated.     AI Rack / Cluster Validation   Own program planning and execution for multi-node and multi-rack scale testing, including test strategy, scheduling, coverage tracking, and readiness gates.   Lead end-to-end delivery of rack-level AI solutions, including compute trays, switch trays, cabling, power, cooling, and management infrastructure.   Ensure rack bring-up plans are executable, resourced, and gated with clear entry/exit criteria across EVT, DVT, and scale phases.   Drive coordination across lab operations, infrastructure, and engineering teams to unblock rack access, power, networking, and test readiness.   Partner with scale, performance, and automation teams to ensure workloads, stress tests, and regressions plans are ready before hardware arrives.     Debug, Failure Analysis & Risk Management   Act as the execution lead for platform debug, coordinating across engineering teams to ensure fast triage, root-cause analysis, and resolution of system-level issues.   Track