Senior Technical Program Manager – AI Agent

Advanced Micro Devices, Inc•San Jose, CA

About The Position

AMD is seeking a Senior Technical Program Manager to lead execution of the AI Agent roadmap in the Intelligence Systems team within AMD AI Group. The role turns algorithmic and agentic research into reliable, scalable, customer-facing software outcomes, reduces operational overhead, establishes execution discipline for complex software flows, and ensures customer-driven work produces durable product and process improvements. The position partners with AI researchers, software engineers, QA, and cross-functional stakeholders to align priorities, stabilize releases, streamline communication, and accelerate delivery of AI capabilities on AMD accelerated compute platforms. The ideal candidate has technical credibility in AI/ML systems and a hands-on execution mindset, and can engage with design documents, model architectures, performance and debugging issues, and complex customer environments while driving clarity, ownership, and predictable delivery across teams.

Requirements

  • Proven TPM leadership delivering complex, cross-functional AI/ML or systems programs end-to-end in ambiguous, fast-changing environments.
  • Strong technical depth to understand and track AI/ML algorithms, performance, system integration, debugging, and reliability issues.

Nice To Haves

  • Experience productizing AI research into robust software deliverables.
  • A master’s or bachelor’s degree in Computer Engineering, Computer Science, or Electrical Engineering is desired.

Responsibilities

  • Own and drive AI Agent roadmap execution from research to productization, including quarterly planning, OKRs, and delivery commitments.
  • Convert research breakthroughs into engineering plans and measurable milestones.
  • Influence prioritization decisions that balance long-term algorithmic advancement with near-term product and customer needs.
  • Drive cross-team execution across algorithm, software, hardware, and platform teams, including synchronized timelines, dependency management, and release readiness.
  • Consolidate customer requests and feedback into durable software features, tooling, test coverage, and process improvements, and ensure learnings are reused across customers.
  • Identify risks, execution gaps, and systemic bottlenecks; implement mitigation plans and ensure teams close them.
  • Facilitate stakeholder communication and present technical progress, risks, and tradeoffs clearly to leadership.
  • Develop metrics and mechanisms to evaluate research impact on customer workloads and revenue, with a focus on continuous improvement.
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