Job Description

Technology Development Phase

Materials Quality Readiness

• Collaborate with the TD team on First of a Kind (FOAK) Materials Quality Readiness, Supplier Quality Programs, and Specification definition—instrumental in ensuring the success of new technode development.
• Leverage AI/ML-driven analytics to assess FOAK material risks, predict failure modes, and accelerate qualification readiness using historical and real-time data.
• Participate, support, and recommend from a Quality perspective on FOAK materials sourcing strategies, including business continuity, benchmarking, new markets, and Quality capability assessment.
• Utilize data-driven insights and predictive modeling to enhance supplier capability assessments and sourcing decisions.
• Support cross-fab technology transfer activities regarding New Technology BOM and drive supplier Quality programs to address Critical Concerns About New, Unique, Different, and Difficult materials.
• Lead cross-functional Category Strategy Team meetings to fan out lessons learned from HVM issues to R&D, align on FOAK materials strategy, ensure closed-loop communication, and prevent recurrence of issues globally.
• Apply AI-enabled knowledge management systems to systematically capture, classify, and disseminate lessons learned across global sites.

HVM Phase

Sourcing, Selection, and Qualification

• Lead quality risk assessments and implement mitigation strategies to support qualification activities.
• Deploy AI-based risk scoring models and digital dashboards to prioritize qualification risks and drive faster decision-making.
• Provide quality-focused input on sourcing and segmentation strategies, including business continuity planning, benchmarking, and supplier selection.
• Incorporate advanced analytics and AI-assisted scenario modeling into RFQ/RFI and supplier selection processes.
• Conduct technical risk assessment audits for new suppliers and materials to evaluate capability and readiness for HVM.
• Leverage digital audit tools and AI-assisted pattern recognition to identify systemic risks and hidden gaps.
• Establish, communicate, and ensure compliance with Supplier Requirements Standards (SRS).

Supplier Development and Excursion Management

• Lead the definition and alignment of global material specifications for Specs Gas & Specs Chem.
• Support development of smart specifications by integrating AI-driven process capability insights and predictive limits.
• Support Material Category Leads in shaping Category Quality Strategy, including Quality Roadmap and Defense Line Program.
• Embed AI/ML use cases into the Quality Roadmap (e.g., predictive excursion detection, automated SPC monitoring, anomaly detection).
• Implement quality programs, benchmarking, and preventive controls aligned with Shift-Left Strategy.
• Facilitate regular Quality and Technical Review (QTR) meetings with suppliers.
• Introduce data visualization and AI-assisted insights into QTRs to drive fact-based discussions and proactive actions.
• Manage supplier and sub-supplier changes through SCM process.
• Oversee resolution of globally impacting photochemical quality issues.
• Utilize AI-driven root cause analysis tools (e.g., pattern mining, correlation analytics) to accelerate issue resolution.
• Collaborate with OCT MTE, Operations, and Facility teams for deep-dive investigations and implement corrective/preventive actions.
• Cascade lessons learned globally to ensure closed-loop prevention.
• Define, track, and monitor monthly supplier quality performance metrics and SRS compliance.
• Develop automated dashboards and AI-enabled performance monitoring systems for real-time supplier scorecards and predictive alerts.
• Continuously improve supplier quality processes to enhance productivity and efficiency.
• Partner with Procurement on supplier evaluations using quality metrics.
• Enable data integration across systems and apply AI analytics to drive objective, data-driven supplier decisions.

Communication & Presentation

• Provide weekly updates on supplier-related activities.
• Maintain strong communication with Global Quality, Procurement, OCT, and cross-functional teams.
• Respond to issues promptly with appropriate escalation.
• Keep stakeholders informed of progress, risks, and opportunities.
• Leverage AI-assisted reporting tools to generate concise, data-driven insights and executive-ready summaries.
• Utilize visualization platforms and automated storytelling tools to enhance clarity and decision-making.

Training and Development

• Take ownership and accountability for achieving goals and completing actions.
• Establish measurable development objectives aligned with corporate priorities.
• Leverage coaching and mentorship for growth.
• Manage time and resources effectively.
• Reflect and continuously improve performance.
• Demonstrate strong commitment to quality and deliver with accuracy and timeliness.
• Show initiative and self-motivation.
• Continuously build AI/data literacy (e.g., understanding ML models, data pipelines, and digital tools) to enhance quality engineering effectiveness.
• Adopt and champion AI-enabled tools and digital workflows within SQE processes.

Growth Opportunity

• Collaborate with global SQEs and cross-regional teams on category initiatives.
• Serve as a key SME in supplier digitalization programs, contributing insights and guidance on AI/ML adoption in supplier quality.
• Lead or participate in development of AI use cases (predictive quality, smart SPC, automated audits, supplier risk intelligence).
• Build deep expertise in material criticality by acting as a primary liaison with suppliers.
• Drive innovation in digital quality ecosystems, including data integration, automation, and AI-enabled supplier collaboration platforms.