I make AI something an enterprise can trust.

I lead AI at BorgWarner from Enterprise IT, supporting functions such as engineering, manufacturing, finance, quality and corporate teams. My work is the strategy, governance and platform foundations that move AI from isolated experiments toward a managed capability.

My starting point is unusual for an AI leader. For more than twenty years I built safety-critical automotive systems, including braking, ABS and LiDAR, where a failure is measured in lives rather than downtime. I developed a safety-specific architecture language that gives traceability from requirements through to testing, and it is used in more than 10 million vehicles. I bring the same discipline to AI: clear accountability, traceable evidence, and governance designed in from the start.

At BorgWarner I helped create the Framework for AI Adoption and Governance, with seven pillars: governance, strategy, reference architecture, toolbox, delivery harness, training and enablement, and communication. I am building the enterprise platform beneath it, from the LLM gateway to the agent runtime, and a focused set of lighthouse projects is proving which patterns scale to production. Before this role I ran our global engineering application estate, from requirements to CAD, CAE and test, where I applied AI to licence management and built an enterprise MCP layer for engineering tools.

Outside the day job I build in the open. Sylang is an AI-native engineering platform for safety-critical products, and I have written a book on the thinking behind it, Sylang: MBSE for AI. I also run my own GPU server for agent experiments, and I write up what I learn every week.

Earlier, I built and led global, multi-site engineering organisations at Continental and Luminar, and worked directly with OEM customers on programme acquisition and acceptance. I have worked in India, Germany and the United States, and I am based in Michigan.