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GM
General Motors
Senior AI Governance Specialist Vehicle Motion Software
Career Insights for Artificial Intelligence Engineer (General)
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What they do
An Artificial Intelligence Engineer develops, tests, and deploys artificial intelligence models. May work closely with data software engineers and data professionals to train and implement AI models into existing systems or develop new applications.
$118,850 / year median in Michigan
Job Description
Engineering Senior AI Governance Specialist - Vehicle Motion Software 위치 Milford, Michigan (+) Show all locations (-) Hide all locations 직무 유형 Full time 게시됨 8 06 2026 Job Requisition
Formal training or certification in ISO 26262 and
JR-202613704
설명Work Arrangement:
Hybrid:
This role is categorized as hybrid. This means the successful candidate is expected to report to Milford, MI three days (Tues., Wed., Thurs.) a week, at minimum.Our Mission:
There's never been a more exciting time to work at General Motors! We are passionate about our bold vision of a world with Zero Crashes, Zero Emissions, and Zero Congestion . Our culture is built on inclusivity, where diverse perspectives are embraced, and every employee can contribute to their fullest potential. We offer flexible and tech-savvy work environments, foster innovation through collaboration, and encourage community engagement through volunteerism.The Role:
The AI Governance Specialist is responsible for establishing, executing, and continuously improving the AI governance framework for vehicle motion software product portfolio. This role provides technical leadership to ensure that all AI elements — whether embedded in vehicle products (e.g., vehicle motion control) or used in the software development process (e.g., AI-assisted requirement generation, test case generation, code tools) comply with applicable automotive safety standards and GM AI policies. The engineer serves as VMEC's primary lead on AI governance methodology and acts as the bridge between software engineering, system safety, and enterprise AI governance bodies.What You'll Do:
Derive and maintain VMEC's AI governance framework from applicable standards includingISO 26262, ISO/PAS 8800, ISO/IEC TR 5469, ISO 21448
(SOTIF), and GM's AI Policy. Establish methodology to classify all AI elements and AI-powered tools within VMEC's scope usingISO 8800
usage levels, distinguishing in-product AI from off-line development AI. Develop and own the VMEC AI Governance Process and documentation aligned with ISO 26262 andISO 8800
requirements. Pilot and scale up the process. Integrate AI governance requirements into existing VMEC software development processes and product lifecycle stages. Interpret and translateISO 26262, ISO/PAS 8800, ISO
21448 andISO/IEC 5469
requirements into actionable VMEC engineering guidance. Conduct gap analyses between current VMEC software processes, GM safety requirements, and applicable AI governance standards; prioritize and drive closure plans. Monitor the evolving AI standards landscape and proactively assess impact on VMEC processes. Maintain a comprehensive inventory of AI elements and AI-powered tools used within VMEC's product and process scope. Lead tool confidence level (TCL) determination per ISO 26262 and ISO 8800, assessing Tool Impact (TI) and Tool Error Detection (TD) for each AI tool in safety-critical workflows. Define and execute tool qualification plans for AI tools requiring qualification (e.g., AI-assisted test case generators, ML model trainers, code generation tools used in ASIL-rated software). Establish criteria and checklists for onboarding new AI tools into VMEC's governed ecosystem. Define and implement AI lifecycle controls encompassing data governance, model development oversight, verification and validation requirements, performance bounds, and operational guardrails. Develop and maintain processes for generating audit-ready AI governance artifacts (AI safety case evidence, tool qualification reports, data governance documentation). Support VMEC's participation in AI tool inventory reviews and compliance assessments. Align with GM's enterprise AI Governance Council, Enterprise Data Governance Office (EDGO), and GM AI Policy compliance requirements including data privacy, security, and export control considerations. Serve as the VMEC subject matter expert for AI safety standards; provide training and guidance to software engineers, system engineers, and leadership on AI governance obligations. Lead and support the VMEC AI Community of Practice (AI CoP) on governance topics; develop and maintain reference materials on ISO 26262 andISO 8800
applicability guidance. Partner with leadership to operationalize governance as an enabler of safe, scalable AI adoption across VMEC. Harmonize VMEC AI governance practices with broader GM standards. Represent VMEC in internal and external AI standards forums as needed. Your Skills & Abilities (Required Qualifications): Bachelor's degree in Electrical Engineering, Computer Engineering, Systems Engineering, Mechanical Engineering, or a related field. 5+ years of experience embedded controls, software safety, or systems engineering for safety critical systems such as automotive or aerospace. Knowledge of ISO 26262 and ISO/PAS 8800, including their interaction and tailoring for AI/ML components. Understanding ofISO 21448
(SOTIF) principles — functional insufficiencies, triggering conditions, and their relevance to AI system performance. Knowledge of GM vehicle safety requirements, ASIL (A-D) determination, and functional safety documentation requirements Understanding of vehicle motion software development processes and toolchains Experience with AI/ML concepts: supervised learning, model training and validation, data quality assessment, uncertainty quantification, bias, and robustness evaluation. Familiarity with tool confidence level (TCL) determination and software tool qualification processes perISO 26262.
Systems thinking — ability to reason across the full vehicle software lifecycle from hazard to control to evidence. Learning agility — keeps pace with rapidly evolving AI standards and technology landscape. Collaboration — effectively partners with safety, software, and program teams; builds trust with technical peers. Communication — translates regulatory complexity into clear, practical guidance for engineering teams. What Will Give You A Competitive Edge (Preferred Qualifications): Master's degree in Electrical Engineering, Computer Engineering, Systems Engineering, Mechanical Engineering, or a related field. 8+ years of experience embedded controls, software safety, or systems engineering for safety critical systems such as automotive or aerospace.Formal training or certification in ISO 26262 and