Yield Development Engineering Manager-Strategic Programs

Intel Corporation•Hillsboro, OR

2d•$224,970 - $374,800•Hybrid

About The Position

We are seeking a Senior Strategic Program Leader to drive the next generation of Yield and Defect Engineering transformation within a high-volume semiconductor manufacturing environment. This role goes beyond traditional engineering leadership serving as a catalyst for AI-driven innovation, enterprise scale program execution, and cross-functional alignment. You will lead a multidisciplinary organization responsible for advancing defect metrology, yield engineering systems, and AI-enabled decision intelligence, ensuring the factory operates with predictive, adaptive, and scalable capabilities. Your leadership will directly shape how data, automation, and artificial intelligence are embedded into daily operations to accelerate yield learning, improve cycle time, and increase productivity. As a key member of the technology and manufacturing leadership team, you will define long-term strategy, influence roadmaps across process integration and metrology, and drive execution of complex, high-impact programs that position the organization for future technology nodes and advanced packaging innovations.

Requirements

Bachelor's degree in Engineering, Physics, Materials Science, Data Science, or related field (advanced degree preferred).
12+ years of experience in semiconductor manufacturing with deep expertise in yield engineering, defect metrology, or process integration.

Nice To Haves

Advanced degree (MS/PhD) in a relevant technical or data-centric discipline.
Experience leading AI/ML transformation initiatives in semiconductor or adjacent high-tech industries.
Familiarity with digital manufacturing ecosystems (data platforms, MES integration, advanced analytics tools).
Track record of defining and scaling enterprise-level engineering systems or platforms.
Strong business acumen with ability to connect technical outcomes to cost, cycle time, and revenue impact.
Experience in advanced packaging technologies (e.g., Foveros, EMIB, heterogeneous integration) is a plus.
Proven track record leading complex, cross-functional programs in high-volume manufacturing environments.
Demonstrated experience driving yield improvement and defect reduction at scale, including ramp and HVM phases.
Strong domain expertise in defect metrology tools, inspection systems, and yield analysis methodologies.
Experience integrating data analytics, machine learning, or AI solutions into engineering workflows.
Exceptional leadership and communication skills with ability to influence across organizational boundaries.

Responsibilities

Define and execute a multi-year strategy for Yield and Defect Engineering, integrating AI/ML, automation, and digital transformation into core workflows.
Lead enterprise-level programs to transition from reactive analysis to predictive and prescriptive yield management systems.
Serve as a thought leader in AI adoption for semiconductor manufacturing, identifying high-value use cases and scaling solutions across sites.
Champion the deployment of AI/Agentic AI solutions to enhance defect detection, classification, excursion prevention, and root cause analysis.
Drive integration of data platforms, digital twins, and advanced analytics into yield and defect systems.
Partner with data science, IT, and automation teams to embed real-time decision intelligence into fab operations.
Oversee yield performance across development and high-volume manufacturing, ensuring alignment to aggressive yield, quality, and delivery targets.
Lead cross-functional efforts to resolve complex yield limiters and defect excursions, minimizing impact to supply.
Institutionalize closed-loop learning systems that accelerate yield ramp and improve defect pareto convergence.
Define and evolve defect metrology strategy, including tool selection, capability roadmaps, and system architecture.
Lead development of scalable defect management systems that enable early detection, excursion containment, and predictive risk mitigation.
Ensure alignment of inspection, review, classification, and analytics ecosystems with future technology requirements
Drive large-scale, cross-site programs requiring alignment across process integration, manufacturing, equipment, and corporate strategy teams.
Operate across multiple disciplines translating executive vision into clear roadmaps, measurable milestones, and disciplined execution.
Influence senior stakeholders and executives to align investments, priorities, and organizational focus.
Build and lead a high-performing, diverse organization, fostering a culture of innovation, accountability, and continuous learning.
Develop next-generation leaders with capabilities spanning engineering depth, data science, and AI fluency.
Champion a shift from individual based to scalable, system-driven excellence.