Advanced Supplier Quality Engineering Lead
General Motors
- Location
- Warren, Michigan, United States of America
- Work model
- On-Site
- Level
- Senior
- H-1B history
- 267 approvals (FY2023)
- Posted
- Sep 16, 2026
Skills
About this role
Job Description
Overview: General Motors’ Global Supplier Quality Advanced Engineering team is transforming how manufacturability and supplier readiness are built into the vehicle development process. The Advanced Supplier Quality Engineering Lead is responsible for identifying and resolving manufacturing, formability, assembly, and quality risks before suppliers are sourced and before issues reach launch or production. The candidate leads critical parts from early product design through tooling, supplier manufacturing readiness, launch, and matching, serving as the eyes and ears for supplier capability and readiness throughout the program. The successful candidate is a highly self-motivated engineer who can connect product design, formability, tooling, assembly, supplier quality, and program timing; make sound technical decisions in complex and fast-paced environments; influence cross-functional teams and suppliers; and use data, digital tools, and approved generative AI responsibly to improve decision-making and execution.
Responsibilities
Lead the Supplier Quality plan and Plan-For-Every-Part for critical parts from early design through matching, ensuring interfaces, datums, variation risks, assembly requirements, supplier alignment, and Product Development Team alignment are established before tooling and production decisions. Execute APQP activities and program reviews, establishing milestones, readiness criteria, risk visibility, owners, escalation paths, closure evidence, and fact-based program-health reporting for leadership. Align product design intent with supplier manufacturing capability early enough to prevent late design changes, tooling rework, launch disruptions, and quality escapes; provide manufacturing-driven feedback to Product Engineering, Studio Design Engineers, and Design Teams for sheet metal stampings, aluminum, ultra-high-strength steel, and related assembly applications. Partner with Formability experts to assess critical parts, interpret results, and resolve risks before design release and supplier sourcing; lead or coordinate reviews of die-face strategy, stamping feasibility, material utilization, press handling, throughput, and potential defects such as splits, wrinkles, surface defects, and skid lines. Participate in die design reviews and use CAD, digital mock-ups, simulation outputs, and technical documentation to ensure manufacturing requirements are reflected in released product and process data and are connected to tooling strategy, supplier capability, and assembly performance. Review supplier assembly processes—including part sequencing, welding, clamping, datuming, checking fixtures, manufacturing methods, GD&T, tooling, and process quality and support technical reviews to determine whether manufacturing and quality plans can reliably meet program requirements. Ensure suppliers understand and comply with applicable GM and industry standards covering materials, body, welding, tooling, assembly, and dimensional requirements; identify out-of-standard conditions before they advance to another process, manufacturing site, or program milestone. Serve as the early technical voice of supplier capability by identifying gaps in equipment, tooling, facilities, process controls, measurement systems, staffing, documentation, and launch preparedness; establish actions, owners, timing, and evidence for risk closure and escalate inadequate plans or commitments. Travel to supplier and GM locations for mini match events and other required reviews; support Supplier Quality Engineers and plant teams with emerging formability, assembly, and manufacturing issues. Coach suppliers, Supplier Quality Engineers, Product Engineers, and other partners on new requirements, techniques, and lessons learned, while using spreadsheets, dashboards, technical reports, shared documentation, and digital collaboration tools to maintain visibility and support fact-based decisions. Use approved generative AI tools, such