MSH PDE PI Manager - HBM NPI

About the role

The MSH PDE Process Integration (PI) Manager leads a team of Process Integration engineers responsible for executing High Bandwidth Memory (HBM) New Product Introduction (NPI) from early development through High Volume Manufacturing (HVM). The role combines people leadership, technical oversight and cross-functional execution, covering PI readiness, yield ramp and risk mitigation across wafer fabrication, assembly and test.

Key responsibilities

• Lead, coach and develop PI engineers across experience levels, set goals and priorities, give regular feedback and plan hiring, onboarding, mentoring and succession
• Own PI execution for HBM NPI programs, balancing resources across programs and ensuring effective NPI-to-HVM handoff
• Review process integration strategies, characterization plans and yield improvement actions, and guide root cause analysis and corrective action
• Escalate and resolve high-risk integration issues and ensure alignment to PI standards and governance
• Act as the primary PI interface to MSH PDE YE, MRDA, Process Engineering, Assembly/Test, Manufacturing and others, communicating status, risks and tradeoffs to senior stakeholders
• Integrate AI-assisted tools into daily work responsibly, and share AI-enabled improvements with the team

Required profile

• Bachelor's or Master's degree in Engineering or a related discipline
• 8-12+ years of semiconductor engineering experience with a strong PI/NPI background
• Demonstrated ability to lead teams, develop talent and manage performance
• Experience with resource planning, prioritization and program execution
• Preferred: prior people-management or senior technical leadership experience, support for advanced packaging, HBM or 3D-stacked technologies, and a track record of yield stabilization during aggressive ramps

Required skills

• Strong communication and decision-making across engineering and leadership teams
• Baseline digital fluency and role-appropriate AI literacy
• Preferred: familiarity with data analytics, yield dashboards or automation initiatives