Senior Supply Chain AI & Analytics Engineer

AMD AMD · Semiconductors · Austin, TX · Engineering

Senior engineer to architect, develop, and operationalize AI-driven analytics solutions for AMD's supply chain, focusing on planning, logistics, and inventory. The role involves building AI agents for monitoring and automation, translating complex problems into data-driven solutions, and partnering with data engineering teams for model deployment.

What you'd actually do

  1. Design, build, and deploy AI/ML models and advanced analytics that improve planning, inventory, logistics, network optimization, and S&OP, while architecting scalable data and analytics solutions that integrate seamlessly with enterprise platforms and supply chain systems.
  2. Develop and operationalize AI agents that continuously monitor supply chain signals, surface proactive insights, recommend actions, and automate decision workflows to enable a more autonomous supply chain environment.
  3. Translate ambiguous and complex supply chain problems into structured, data-driven solutions by performing exploratory analysis, scenario modeling, root‑cause investigations, and optimization across large datasets.
  4. Create high‑quality dashboards, semantic models, and KPI frameworks in Power BI; enable search‑driven and natural‑language analytics through ThoughtSpot; and establish best practices for visualization and data storytelling.
  5. Partner closely with data engineering teams to ensure reliable, well‑modeled datasets, while supporting pipeline development, feature engineering, and model deployment to production with an emphasis on scalability, explainability, and maintainability.

Skills

Required

  • Python and/or R
  • building and deploying AI/ML models
  • generative solutions
  • AI agents
  • Power BI
  • ThoughtSpot
  • scalable data and analytics solutions
  • planning, logistics, inventory, network optimization, S&OP
  • feature engineering
  • deploying models/agents into repeatable, maintainable operating environments
  • LLMs
  • prompt engineering
  • enterprise agent frameworks
  • design solutions that are explainable and user-friendly

Nice to have

  • semiconductor supply chain
  • optimization techniques
  • ERP systems such as SAP

What the JD emphasized

  • AI agents
  • AI/ML models
  • AI agents
  • AI/ML models
  • AI agents
  • AI agents

Other signals

  • architecting scalable data and analytics solutions
  • Develop and operationalize AI agents
  • automate decision workflows
  • deploying AI/ML models, generative solutions, or AI agents