Quality Supervisor- Future Model

Role overview

Architecture and quality strategy

• Identify architectural improvements that prevent quality issues and embed quality into future vehicle architectures with engineering and product teams.
• Drive Built-In Quality principles across hardware, electrical, software, and mechatronic systems.
• Develop long-term quality roadmaps and translate lessons learned into platform-level standards, requirements, and design practices.

Benchmarking and defect prevention

• Benchmark competitor vehicles, technologies, architectures, and quality performance; identify best practices and emerging trends.
• Develop architecture and design recommendations from benchmarking insights.
• Lead enterprise-wide defect prevention and global read-across; ensure quality concerns from current programs inform future architectures.

Analytics and cross-functional leadership

• Evaluate quality trends, warranty data, customer feedback, and engineering metrics; support risk assessments and develop executive recommendations.
• Collaborate with product development, systems engineering, launch, manufacturing, supplier quality, and technical platform teams.
• Influence strategic decisions and build capability in quality-by-design and defect prevention.

Required qualifications

• Bachelor’s degree in software engineering, electrical engineering, computer science, data science, systems engineering, mechanical engineering, or a related field.
• 10+ years in automotive systems, software, electronics, quality, systems engineering, product development, or a related technical discipline, including cross-functional delivery experience.
• Experience managing technical programs or projects, defining metrics, building dashboards, and using data to improve performance and issue resolution.
• Experience using, supporting, or deploying AI-enabled or digital solutions and translating operational problems into practical use cases.
• Working knowledge of vehicle electronics and software, architecture, interfaces, diagnostics, failure modes, and system-level troubleshooting.
• Ability to lead or coordinate a small team, develop others, and deliver through disciplined execution and influence.

Additional qualifications

• A relevant master’s degree or project management certification such as PMP is preferred.
• AI, analytics, or automation delivery; matrixed team leadership; forward-model or new-vehicle quality; prototype and launch readiness are beneficial.
• Familiarity with generative AI, machine learning, intelligent automation, evaluation, and responsible-AI controls is beneficial; human review is expected before AI outputs influence quality decisions.
• Hackathon, pilot, or rapid-experiment experience is beneficial.

Workplace

• The position is hybrid and requires working onsite four or more days per week.

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