Head of AI Engineering Productivity, Global Cluster Engineering

AMD
Seattle, Santa Clara, Austin
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningEducation: bachelorsSkills: ["Leadership","Strategic planning","Collaboration","Execution excellence"]

Lead AI enablement to accelerate adoption of agentic systems across AMD’s software and hardware engineering workflows. Define and execute an AI strategy spanning engineering lifecycles, cluster validation, and delivery. Drive adoption of AI copilots and autonomous agents, build scalable AI platforms and APIs, and establish best practices for model integration, evaluation, deployment, governance, and operationalization to measurably improve productivity and developer velocity.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
AMD
AMD
1 month ago

Head of AI Engineering Productivity, Global Cluster Engineering

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 7 hours agoStatus: Live

Job Summary

Lead AI enablement to accelerate adoption of agentic systems across AMD’s software and hardware engineering workflows. Define and execute an AI strategy spanning engineering lifecycles, cluster validation, and delivery. Drive adoption of AI copilots and autonomous agents, build scalable AI platforms and APIs, and establish best practices for model integration, evaluation, deployment, governance, and operationalization to measurably improve productivity and developer velocity.
Location: Seattle, Santa Clara, Austin
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Sr. Director level

Key Responsibilities

  • •Define and execute AMD’s AI enablement strategy across software engineering, hardware development, validation, operations, and business functions.
  • •Lead adoption of AI copilots, autonomous agents, and intelligent workflows throughout the engineering lifecycle.
  • •Deploy agentic systems that triage issues, route work, and propose solutions across large-scale engineering environments.
  • •Build scalable AI platforms, APIs, frameworks, and services to accelerate safe, effective AI adoption across teams.
  • •Establish best practices for AI model integration, evaluation, deployment, governance, and operationalization.

Key Requirements

  • •Deep expertise in AI/ML systems, Large Language Models (LLMs), agentic architectures, and AI-native developer workflows.
  • •Hands-on experience with agent frameworks, orchestration, memory architectures, evaluation systems, and model deployment.
  • •Experience delivering platform-level products and production-ready AI solutions in large-scale engineering organizations.
  • •Expertise implementing intelligent automation, including automated bug triage, issue routing, workflow automation, and conversational AI.
  • •Bachelor’s degree in a technical field; Master’s or PhD preferred.
Experience:AI/MLLarge Language ModelsAgentic systemsPlatform engineeringEnterprise engineering
Education:Bachelor's in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, Machine Learning, Software Engineering, or a related technical field
Skills:LeadershipStrategic planningCollaborationExecution excellence
Languages:English
Tech Stack:Large Language Models (LLMs)Agentic architecturesAI copilotsAutonomous agentsAI platformsAPIsTool orchestrationMemory architecturesModel evaluationModel deploymentMultimodal modelsOpen-source AIInference efficiencyWorkflow automationKnowledge retrieval

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

AMD
Designs and produces semiconductor products including CPUs, GPUs, and adaptive SoCs for consumer, enterprise, and embedded markets, competing across PCs, data centers, and gaming industries.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1969
Glassdoor
Glassdoor: 3.9
WebsiteLinkedIn