Vivek Gupta

Scaling engineering teams is one of the hardest jobs in tech - and most of the pain is invisible until it isn't. At CoinDCX, I led engineering through one of India's fastest hyper-growth phases - taking the team from 15 to 200+ engineers while the company grew from $30M to $2B in valuation. We built fast, shipped constantly, and operated in a high-stakes, regulated environment where downtime wasn't an option. What I learned the hard way: as engineering complexity grows, the systems and tools teams rely on don't grow with them. Incidents get harder to diagnose. Costs spiral quietly. Delivery slows in ways that are hard to explain to the business. And engineering leaders spend more time firefighting than building. I tried to solve this at CoinDCX - we built internal tooling, refined processes, and used data to drive better decisions. It worked. But it was hard, expensive, and shouldn't have to be custom-built by every engineering org from scratch. That's the problem I'm now building a solution for. I'm working on an AI-native platform for engineering operations - designed specifically for fast-scaling startups where engineering complexity has outpaced the tools available to manage it. If you're an engineering leader thinking about incident management, infrastructure costs, delivery intelligence, or how AI fits into your ops stack - I'd genuinely love to talk. Not to pitch, just to exchange notes.