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Head of AI Engineering Productivity, Global Cluster Engineering

AMD· Engineering
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Hybrid (Seattle, WA / Santa Clara, CA / Austin, TX)$240k - $360kFull-timePosted 3mo ago

About the role

Lead AI enablement and accelerate adoption of agentic systems across software and hardware engineering workflows. Individual contributor role at the apex of AMD’s cluster innovation, focusing on measurable productivity improvements and scalable AI-driven workflows.

Responsibilities

  • Define and execute AMD’s AI enablement strategy across software engineering, hardware development, validation, operations, and business functions.
  • Lead the adoption of AI copilots, autonomous agents, and intelligent workflows throughout the engineering lifecycle.
  • Deploy agentic systems that autonomously triage issues, route work, and propose solutions across large-scale engineering environments.
  • Build scalable AI platforms, APIs, frameworks, and services that accelerate safe and effective AI adoption across teams.
  • Establish best practices for AI model integration, evaluation, deployment, governance, and operationalization.
  • Develop reusable agent frameworks that support tool orchestration, memory management, workflow automation, and customization.
  • Identify opportunities to replace manual processes with intelligent, AI-driven workflows that improve efficiency and scalability.
  • Drive measurable improvements in engineering productivity, developer velocity, hardware validation cycles, and organizational effectiveness.
  • Enable AI-powered capabilities such as documentation generation, onboarding assistants, knowledge retrieval, and workflow automation.
  • Transform internal support functions through conversational agents capable of executing tasks across business operations.
  • Partner with engineering, research, infrastructure, and product leaders to identify priorities and accelerate AI adoption.
  • Collaborate with external partners, model providers, infrastructure vendors, and open-source communities to incorporate best-in-class technologies.
  • Optimize AI platform performance, inference efficiency, and operational cost at scale.
  • Evaluate emerging AI ecosystems, multimodal models, development tools, and agentic technologies to guide strategic investments.

Qualifications

  • Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, Machine Learning, Software Engineering, or a related technical field; Master’s, PhD degree preferred.

Skills

Required:AI enablement strategyAgentic systemsAI copilots and autonomous agentsAI platform developmentModel governance and deploymentMemory management and tool orchestrationAutomation and workflow optimization
Nice to have:Documentation and onboarding automationKnowledge retrieval systems

Benefits

  • Benefits offered are described: AMD benefits at a glance.
Last updated Oct 15, 2026. Interested? Apply on the company site.
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AMD delivers leadership high-performance and adaptive computing solutions to advance data center AI, AI PCs, intelligent edge devices, gaming, & beyond.

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