Senior Engineer, Wafer Quality Assurance

Requirements

• Excellent communication and presentation skills
• Experience with end-to-end quality management in semiconductor manufacturing
• Hands-on experience developing AI agents or decision-automation tools (e.g., using Python, LangChain, or similar frameworks)
• Salary Range:
• 81,000.00-108,000.00
• #LI-JS1
• Compensation & Benefits Details
• An employee's pay position within the salary range may be based on several factors including but not limited to (1) relevant education; qualifications; certifications; and experience; (2) skills, ability, knowledge of the job; (3) performance, contribution and results; (4) geographic loca

Additional Information

ESSENTIAL DUTIES AND RESPONSIBILITIES AI Platform Change Control & Quality Assurance: Serve as the quality gatekeeper for AI platform changes. Develop a deep understanding of system interdependencies, drive requirements gathering (including testing and verification protocols), and collaborate closely with wafer operations partners to ensure seamless, quality-compliant implementations. End-to-End Wafer Quality Program Support: Support the full lifecycle of wafer quality initiatives, including Change Review Board (CRB) margin projects and Material Review Board (MRB) processes, ensuring consistent quality standards from start to finish. Agentic AI Development for Quality Operations: Design and build Agentic AI solutions with autonomous decision-making capabilities for Incoming Quality Assurance (IQA) and Outgoing Quality Assurance (OQA) processes across wafer operations. Failure Mode & Effects Analysis (FMEA): Lead and facilitate FMEA activities across IT and wafer systems to proactively identify, assess, and mitigate potential failure modes and their impact on quality and reliability. REQUIRED Bachelor's degree in Engineering, Computer Science, Data Science, or a related technical field (Master's preferred) 3+ years of experience in quality assurance, quality engineering, or a related role within semiconductor or wafer manufacturing Working knowledge of AI/ML platforms and an understanding of change control processes in production environments Experience with or exposure to Agentic AI, LLM-based systems, or intelligent automation frameworks Familiarity with FMEA methodology and its application to IT and manufacturing systems Strong cross-functional collaboration skills with the ability to engage both technical and operations teams Excellent analytical and problem-solving skills with a detail-oriented mindset

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Company Intel

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