Manager- AI Transformation, Cpu Diagnostics and Validation

AMD AMD · Semiconductors · Bangalore, India · Engineering

Manager for CPU Diagnostics and Validation team in Bangalore, responsible for post-silicon validation, SLT manufacturing stress content, CReST pattern development, and RMA debug. The role also involves embedding AI into the team's operating model to identify use cases, scale AI solutions, accelerate engineering productivity, improve debug efficiency, and enhance data-driven decision making. This includes defining and driving the team's AI strategy within diagnostics and validation flows, piloting and scaling AI use cases, and ensuring AI adoption across global sites.

What you'd actually do

  1. Lead and grow the Bangalore team, including hiring, onboarding, goal setting, coaching, and performance management, while setting clear expectations for AI fluency and AI-assisted execution across the organization.
  2. Own weekly and quarterly execution plans across key Bangalore deliverables, including:
  3. Post-silicon validation content development, with a focus on improving coverage, efficiency, and reuse through automation and AI-assisted workflows where appropriate.
  4. SLT stress content for manufacturing readiness and quality, including opportunities to apply data analytics and AI-driven insights to improve coverage and issue detection.
  5. RMA debug, failure reproduction, and root-cause acceleration, leveraging AI and data-driven techniques to improve triage speed, failure signature analysis, and insight generation.

Skills

Required

  • CPU validation and diagnostics expertise
  • People leadership
  • Structured, delivery-oriented approach
  • Balancing urgent debug demands with long-range content roadmaps
  • Coaching engineers
  • Establishing disciplined operating rhythms
  • Influencing cross-functional teams across geographies
  • Systems-level thinking
  • Data-driven decision making
  • Clear executive communication
  • AI-forward mindset
  • Translating emerging AI capabilities into practical engineering value
  • Championing responsible experimentation
  • Prioritizing scalable use cases
  • Building team expectations around adopting AI
  • Post-silicon validation content development
  • SLT stress content
  • CReST patterns for wafer sort (WS) and final test (FT)
  • RMA debug, failure reproduction, and root-cause acceleration
  • Rigorous tracking for milestones, dependencies, risks, and recovery plans
  • Partnering with technical leads to prioritize work, balance resources, and maintain common quality standards
  • Improving engineering productivity through process standardization, reusable frameworks, intelligent automation
  • Defining and driving the team’s AI strategy within diagnostics and validation flows
  • Technical rigor through review mechanisms, content quality gates, model and workflow validation
  • Representing execution in global reviews and communicating concise updates
  • 10+ years in CPU or semiconductor post-silicon validation, diagnostics, test, or product engineering
  • 3+ years of direct people management experience
  • Demonstrated ownership of complex, cross-functional delivery programs
  • Strong understanding of manufacturing test ecosystem
  • Experience in debug and failure analysis workflows
  • Strong working knowledge of AI/ML techniques, data analytics, and modern engineering tooling (for example Python-based analytics, model proto

What the JD emphasized

  • AI transformation
  • AI thinking
  • AI solutions
  • AI to accelerate
  • AI to improve
  • AI-driven decision making
  • AI fluency
  • AI-assisted execution
  • AI-assisted workflows
  • AI-driven insights
  • AI and data-driven techniques
  • AI-assisted reporting
  • AI adoption practices
  • AI strategy
  • AI use cases
  • AI-enabled improvements

Other signals

  • embedding AI into operating model
  • scaling practical AI solutions
  • AI to accelerate engineering productivity
  • AI to improve debug efficiency
  • AI-driven insights
  • AI strategy within diagnostics and validation flows
  • piloting and scaling of high-value use cases