Global Director of Quality and AI Innovation

Job Description Summary

We are looking for a senior-level Quality Leader or Quality Director with a strong managerial background in Quality within complex, global manufacturing environments, combined with direct experience in implementing Artificial Intelligence (AI) and Machine Learning (ML) solutions in the field of Quality Management.

Job Description

Essential Responsibilities

• Lead the development and continuous improvement of quality processes at the Electrification Systems level, including Non-Conformance (NC) management, FMEA, Root Cause Analysis (RCA), and supplier quality processes.
• Drive the adoption of advanced data analytics, AI, and Machine Learning techniques to enhance quality monitoring, predictive analytics, and process optimization.
• Develop and implement the digital quality roadmap, ensuring integration with evolving business needs and technology trends.
• Collaborate with cross-functional teams such as Test Engineering, Quality, Sourcing, Procurement, and Manufacturing to ensure seamless execution of New Product Introduction (NPI) and Life Cycle Support (LCS) projects.
• Lead change management and continuous improvement initiatives, using lean principles and data-driven insights to close performance gaps.
• Provide leadership, mentorship, and technical guidance to the HQ Quality team and broader Electrification leadership.
• Partner with internal and external stakeholders to identify best practices, leverage industry trends, and enhance Grid Solutions' competitive quality position.

• Solid knowledge of Artificial Intelligence (AI) and Machine Learning (ML) concepts and proven practical experience applying them to quality processes. This is a mandatory requirement for consideration.
• Master's or PhD degree in Engineering, Computer Science, Electrical Engineering, Mathematics, Statistics, or related fields.
• Several years of proven leadership experience within Quality Management, with a track record of guiding teams and projects to successful outcomes in manufacturing environments.
• Demonstrated expertise in quality process development and management, including Non-Conformance (NC) handling, FMEA, Root Cause Analysis (RCA), and supplier quality processes.
• Advanced skills in scientific data analytics and digital tools (e.g., Python, R, Tableau, Power BI), with the ability to lead AI, Machine Learning, and advanced analytics initiatives that drive transformation in quality systems.
• Experience in developing and implementing digital quality strategies, including ownership of digital quality roadmaps.
• Familiarity with and application of change management methodologies (e.g., SAFe) within multinational or complex matrixed organizations.
• Strong communication and interpersonal skills, with the ability to influence and align stakeholders across all levels of the organization.