AI Engineer

I build AI systems that directly impact revenue. At Bicycle AI, I'm architecting an intelligent analytics platform that serves as an autonomous analyst for revenue teams across Travel, eCommerce, Delivery, and Fintech. The system monitors business performance, identifies anomalies before they become problems, and delivers actionable recommendations. My work spans understanding what business leaders need, designing AI workflows that generate insights autonomously, and ensuring those insights reach the right people.

Before this, I was part of the founding engineering team at Publicis Sapient that built Slingshot — a GenAI-powered engineering platform now contributing to a $55M deal pipeline with clients like Lloyds and ADCB. I was deployed on-site with the Saudi Arabian government as a forward deployed engineer, piloting AI-driven digital transformation with emphasis on Arabic language enablement. I've learned that the best engineering is invisible; what matters is whether the business problem got solved.

My foundation is in research-grade machine learning. I've published work on interpretable ML at IIT Delhi, built Graph Neural Network frameworks at the University of Warwick, and designed computer vision systems at RMIT University. This research mindset shapes how I build production AI — systems that users can't trust won't get adopted, no matter how technically impressive.

I also bring context beyond engineering: I spent time on the investment team at Avatar Growth Capital, evaluating $10-30M growth-stage SaaS deals — which taught me what metrics matter to investors, how product-market fit gets evaluated, and why some AI products capture value while others become features. I've also built quantitative models at Torch Investment Management in Singapore, applying ML to financial markets.

Combined with enterprise consulting and a research background, I'm most useful where problems are ambiguous and require moving fluidly between strategy and implementation.