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Director of AI Engineering @ Ford Motor Company | Building AI Products that Save Costs, Drive Revenue, Increase Efficiency & Scale
I build AI products that solve real business problems at scale. At Ford, I lead a portfolio of AI capabilities across the aftersales ecosystem — spanning warranty, claims, and extended service — helping the organization grow revenue, cut costs, and operate smarter. My work sits at the intersection of AI engineering, business strategy, and systems design. I believe in AI systems — products that integrate with real workflows, scale across functions, and create durable value. Over 10+ years, I've built and shipped ML platforms, computer vision systems, and enterprise data products used across large organizations. I've also built the teams and cultures that make that possible — developing AI leaders, driving cross-functional alignment, and making complex ideas accessible to executives and engineers alike.
University of Michigan - Stephen M. Ross School of Business
Master of Business Administration - MBA
N/A – Present
Illinois Institute of Technology
Master's degree, Computer Science
N/A – Present
Visvesvaraya Technological University
Bachelor's of Engineering, Information Technology
N/A – Present
Ford Motor Company
Director of AI Engineering
April 1, 2026 – Present
Hybrid
Ford Motor Company
Senior AI Manager | Ford
October 1, 2024 – April 1, 2026
Hybrid
Ford Motor Company
AI Manager | Ford Artificial Intelligence Advancement Center
April 1, 2022 – September 1, 2024
Hybrid
Ford Motor Company
AI Lead | AI advancement center - Computer Vision
April 1, 2021 – September 1, 2021
Ford Motor Company
AI/ML Software Engineer | AI Advancement Center
June 1, 2019 – April 1, 2021
Microsoft
Software Engineer | Machine Learning
July 1, 2018 – June 1, 2019
Redmond · On-site
HCL Technologies
Machine Learning Engineer
May 1, 2017 – May 1, 2018
Redmond · On-site
Infosys
Software Engineer
September 1, 2011 – July 1, 2016
Bengaluru, Karnataka, India · On-site
Ethics of AI
The London School of Economics and Political Science (LSE)
June 24, 2026 – Present
Google Cloud Certified Cloud Digital Leader
June 24, 2026 – Present
Google Cloud Digital Leader Training
Coursera
June 24, 2026 – Present
AWS Certified Machine Learning – Specialty
Amazon Web Services (AWS)
June 24, 2026 – Present
DataScience with Neo4j
Neo4j
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's extensive experience is heavily concentrated in AI/ML engineering and leadership, with a clear progression within large organizations (Ford, Microsoft, HCL, Infosys). While their technical depth in AI is significant, their target role is 'Data Analyst'. This represents a significant mismatch in scope and responsibility. Their experience is geared towards leading and building AI systems, not primarily performing data analysis. The project diversity is limited as no projects were provided, and the skills listed are primarily high-level strategic AI rather than specific data analysis tools or techniques. This indicates a potential misalignment with a pure Data Analyst role, suggesting they might be overqualified or seeking a different type of challenge than a typical Data Analyst position.
Soft Skills & Operational Fit
The candidate's career progression at Ford, leading multiple AI initiatives and teams, suggests strong leadership, strategic thinking, and cross-functional collaboration skills. Their focus on translating complex business challenges into scalable AI products indicates a practical, results-oriented approach. The descriptions highlight fostering a culture of curiosity, accountability, and continuous learning, which are positive indicators for operational fit.