Job Details:

Job Description:

The Role and Impact

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.

Key Responsibilities
Strategic Leadership and Transformation:

• 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.

AI-Driven Productivity and Decision Intelligence:

• 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.

Operational Excellence and Yield Performance:

• 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.

Defect Metrology and Systems Leadership:

• 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

Program Execution and Stakeholder Influence:

• 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.

Organization and Talent Leadership:

• 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.

Qualifications:
Minimum Qualifications
• 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.
• 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.

Preferred Qualifications
• 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.

Join our team and be part of shaping the future of technology through your leadership and expertise. Apply today to make an impact.

Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.

Job Type:
Experienced Hire

Shift:
Shift 1 (United States of America)

Primary Location:
US, Oregon, Hillsboro

Additional Locations:
US, Arizona, Phoenix

Benefits

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.

Annual Salary Range for jobs which could be performed in the US: $265,480.00-374,800.00 USD

The range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific compensation range for your preferred location during the hiring process.

Work Model for this Role
This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.