Senior Supply Chain AI & Analytics Engineer

About the role

At AMD, we are looking for a senior individual contributor to help architect, develop, and operationalize AI-driven analytics solutions that transform our end-to-end supply chain. The role involves working across planning, logistics, inventory, transformation, and factory operations to turn complex challenges into actionable insights and autonomous decisioning.

Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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.
• Collaborate across Supply Chain, IT, and Transformation teams to align analytics initiatives with business priorities; communicate insights effectively to technical and non-technical audiences; mentor junior contributors; and operate fluidly in a global, fast-changing environment requiring flexibility across time zones.

Requirements

• Expertise in Python and/or R, with hands-on experience building and deploying AI/ML models, generative solutions, or AI agents that automate insights, recommendations, or actions.
• Strong capability in Power BI (data modeling, DAX, semantic layer design) and familiarity with ThoughtSpot or similar search/NLQ analytics tools.
• Demonstrated ability to architect scalable data and analytics solutions, integrating models, pipelines, and AI agents with enterprise platforms and supply chain systems.
• Experience with feature engineering, production pipelines, and deploying models/agents into repeatable, maintainable operating environments.
• Knowledge of optimization techniques (linear programming, heuristics) and experience integrating analytics with ERP systems such as SAP.
• Exposure to LLMs, prompt engineering, and enterprise agent frameworks, with the ability to design solutions that are explainable and user-friendly.
• Ability to work effectively in global teams, manage shifting priorities, collaborate across functions, and communicate clearly with leadership and technical partners.

Qualifications

• Bachelor’s or master’s degree in data science, Engineering, Operations Research, Supply Chain, Computer Science, or related field.

Skills

• Technical depth in AI/ML, data science, and analytics.
• Strong communication and collaboration skills.
• Ability to work in a fast-paced, ambiguous environment.
• Experience with supply chain, logistics, and inventory management.

Benefits

The benefits offered are described: AMD benefits at a glance.