I turn messy, workflow-heavy problems into AI-driven products people actually use, building automation, analytics, and web + mobile experiences for streaming and media clients like JioStar, Disney, National Geographic, Star, and Colors.
I've spent nearly 3 years building products where the challenge usually isn't "build a feature." It's making a complex process faster, simpler, and more scalable, while keeping the people using it at the center.
At Planetcast Media Services, I work on AI-driven Media Asset Management products used by major streaming and broadcast teams, including JioHotstar, Amazon Prime, Disney, National Geographic, Colors, and Star, across workflow automation, analytics, and web + mobile experiences. Before that, I got hands-on across the full product lifecycle at Desynova, and cut my teeth in data analytics at Atlas Copco Group.
My foundation spans engineering (B.Tech ECE, VIT Vellore) and business strategy (MBA, IIM Nagpur), which mostly means I can move between technical constraints, customer problems, and business goals without missing a beat.
Own 0→1 development of AI-driven MAM capabilities for enterprise streaming and broadcast clients including JioHotstar, partnering with AI/ML, Android, and iOS engineers to ship workflow automation across web and mobile. Built a live analytics dashboard giving leadership real-time visibility into platform activity, and led the 2026 migration scaling premium formats (4K, HDR, Dolby Vision/Atmos) while cutting publishing TAT by 15%.
Led GenAI-powered subtitle generation for regional content, working directly with AI/ML engineers on model accuracy and throughput, while running sprints as Scrum Master. Ran competitor research and customer discovery, then shipped low-code configuration that cut engineering dependency for enterprise customizations.
Built a training-effectiveness measurement system based on the Kirkpatrick model, with Power BI dashboards for L&D stakeholders.
My wife and I could never agree on what to watch or where to eat. Every night turned into the same "I don't know, you pick," so I built something to end it. Everyone in the group swipes privately on the same options, and whoever matches the most wins, no more back and forth. It worked well enough that I scaled it past the two of us: friend groups, roommates, and family trips of up to 10 people now use it to stop arguing too.


I'm open to product roles where I can help build, ship, and improve what your team is working on, from messy 0→1 problems to scaling what already works. If you want someone who moves comfortably between engineering, business, and the people actually using the product, let's talk.