Own and execute the end-to-end AI strategy across Technology and Products, aligned to business priorities and delivered in close partnership with enterprise stakeholders—driving measurable improvements in productivity, quality, and cycle time.
Lead AI-enabled and software engineering transformation across the full technology-to-product lifecycle, including agentic workflows, simulation-driven decision-making, predictive analytics, and closed-loop learning systems that accelerate execution and improve first-time-right outcomes.
Drive and integrate cross-functional AI initiatives spanning: New DRAM, NAND, and Advanced Packaging Technology Silicon Design for Memory and Logic End-to-End Silicon Life Cycle Engineering DRAM Module and SSD Development Engineering Productivity Platforms and AI solutions.
Architect, implement, and scale enterprise-grade Engineering AI platforms and engineering software solutions that support core workflows and mission-critical use cases, with strong foundations in security, reliability, and governance.
Provide AI technology leadership and pathfinding, maintaining an external perspective on emerging AI innovations and translating advanced capabilities into practical, high-impact engineering solutions.
Build and lead a robust external AI ecosystem, establishing strategic partnerships with leading AI companies, EDA vendors, academic institutions, and emerging startups.
Establish clear value realization and accountability, defining success metrics, tracking benefits, and providing executive-level reporting for AI investments.
Foster AI upskilling and an AI-driven culture across all global TPG functions, enabling broad adoption while ensuring responsible and secure use of AI technologies.
Partner closely with the Micron AI Steering Committee and the Transformation Officer to shape and execute a coherent, company-wide AI strategy.
Requirements
Senior executive leadership experience driving AI, data, or advanced analytics at enterprise scale.
Proven track record delivering measurable productivity and cycle time improvements in complex engineering or product development environments.
Deep understanding of AI/ML technologies and platforms with the ability to translate strategy into scalable execution.
Background in semiconductor technology, silicon design, hardware, software, manufacturing, or systems-level engineering environments.
Experience establishing governance, security, and compliance frameworks in regulated enterprise environments.
Strong executive presence with the ability to influence across functions and levels.
Experience leading large, globally distributed technical organizations.
Demonstrated success balancing innovation with enterprise risk management.