What does a typical day look like for a Chief AI Product Officer? 

If I had to break down a typical day: around 30% goes into implementation support, either forSaaS or guiding the team on building AI journeys for clients. The next 30% is for the tech and product team thinking about new features and how to take those forward. The rest of the time goes into acquiring new or potential customers. No day is really the same, and that's what I enjoy about working in startups.

Life can become a bit monotonous when you're in more established companies, like when I was at Sabre. It gets bogged down by office politics rather than actually building or doing things. I like the chaotic element of startups.

What is a common misconception about working in AI or product management that you wish more students would understand?

A lot of fresh grads think AI is about just implementing Python. But if you don't understand the statistics behind it like vector spaces, how models work, or even basic math you can't fully leverage it. You'll just be a Python engineer.

To be an actual AI engineer, you must understand business and data science. Otherwise, you won't even know whether the output your model gives is correct.

You graduated with a mechanical engineering degree and went straight into Mu Sigma, diving into analytics. What was going through your mind back then? Did you know you were going to pivot out of mechanical engineering?

A few of my batchmates joined Mu Sigma, and I realized they didn't discriminate based on your degree. You just had to understand analytics, which meant business analytics, some stats, and basic programming.

It kind of reset things; everyone was on the same page once you joined. They put a lot of responsibility on you early on and threw you into the deep end. And that felt right. It combined a lot of the things I enjoyed.

What key features of BITS Pilani Goa made you feel that you have come to the right place?

Studying at BITS Pilani Goa was a truly enriching experience for me. The campus was filled with students who had made it purely on merit, which naturally raised the bar for competition and constantly pushed us to put in our best effort. What made it even more special was the diversity of the student body; people came from all over the country, each bringing unique perspectives and skills. I ended up learning so much outside of the academic curriculum, from casual conversations about the stock market to late-night discussions on entrepreneurship and tech. It wasn't just about textbooks—it was a complete learning ecosystem.

One part of your journey that really caught my attention was Pangea Tech. Can you explain what Pangea Tech does and the reason behind starting the company?

My colleagues and I decided to create an Explainable AI product, a platform that uses SHAP models to demonstrate what neural networks are actually doing under the hood. The idea was to peel back the layers and give users a transparent view into the decision-making process of neural networks. With the help of SHAP, we were able to visualize the internal workings and identify which features influenced a particular decision. Our goal was to make AI less of a black box and more of an understandable system, especially for people who might be skeptical or curious about how these models come to conclusions.

What piece of advice would you give to a fellow BITSian who wants to end up in a similar position as yours?

One of the things I truly admire about BITS Pilani is that it doesn't just train engineers; it cultivates technocrats. The culture here encourages exploration beyond the boundaries of your own discipline. No one is restricted from attending classes outside their branch, and that kind of academic freedom really sets BITS Pilani apart. I was able to dive into subjects that were not part of my core curriculum just out of pure interest, and that helped me develop a much more holistic understanding of technology and its real-world applications.