Quality Engineering must become Trust Engineering — validating not just whether software works, but whether AI systems can be governed, explained, and defended.
Most AI programmes don't fail because of bad technology — they fail because the operating model wasn't built to match. Winning in the AI era means shipping with confidence that's engineered, not asserted.
Before advising independently, I spent 28 years in enterprise delivery leadership — most recently as Global Head of Quality Engineering at LTIMindtree and Movate Technologies, scaling a $350M+ practice to 7,500+ professionals and earning Forrester and NelsonHall Leader positioning in AI Assurance. I now bring that operating discipline to enterprises that need their AI to be trustworthy — not just functional.
Led enterprise AI-readiness and QE assessments across PE-backed portfolio companies and EdTech clients, targeting 20–60% efficiency and throughput gains.
Architected and deployed a 20-agent AI QE platform spanning AI-assisted testing, autonomous automation, and defect prediction.
Introduced ML/NLP-driven test data management, cutting data generation time by 60%.
Delivered AI-infused test automation across a 15-brand portfolio, cutting test cycle time by 30–40%.
Built a platform-led delivery model generating $1.5M+ in annualised savings.
Led a QE transformation to zero production defects, 70%+ automation, and $1.2M+ in annual savings.
Grew a $70M+ account portfolio by 300%+ in five years, anchoring a $40M+ AI-led QE expansion.
Closed two independent AI-driven QE deals exceeding $50M each.
Ran one of the industry's largest QE practices: $350M+, 7,500+ professionals, 360+ customers, zero major delivery disruptions.
Named a Leader in AI Assurance QE by both the Forrester Wave and NelsonHall NEAT.
Happy to walk through how this track record would translate to your organisation.