Artificial Intelligence

• Lead the architecture and development of AI platforms focused on internal process excellence
• Partner with the Automotive Principal Architect to define architecture, tools, and processes for AI/ML adoption globally
• Manage a team of five AI practitioners and mentor global teams implementing AI solutions
• Design and implement advanced AI solutions requiring cross–value-stream orchestration
• Lead development of end-to-end data platforms for agentic AI training, evaluation, and reinforcement
• Build scalable, real-time pipelines to ingest, transform, and store multimodal data (text, logs, user interactions, actions, environments)
• Design dynamic memory and knowledge systems (vector stores, graph DBs, memory stores)
• Collaborate with researchers to integrate live feedback, human-in-the-loop data, and auto-labeling systems
• Own data governance, quality, and security policies for self-improving AI agents, aligning with global standards
• Build observability tools for agent behavior and decision tracking (lineage, reproducibility, versioning)
• Mentor junior engineers and cultivate a high-performance engineering culture
• Stay ahead of AI infrastructure trends and incorporate best practices into roadmaps
• Act as subject matter expert for AI engineering internally and externally
• Manage budgets for AI tools and measure value generated vs. costs
• Drive ecosystem partnerships, vendor management, and executive-level influence to advance adoption
• Success measures: division-wide AI adoption; delivery of scalable, enterprise-grade platforms; number of production AI agents driving measurable efficiency and effectiveness gains

Director, AI Chief Engineer – Process Excellence

Senior AI Analyst

IT Director – Decision Intelligence, AI-First Transformation

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AVP, AI Governance