I moved from IIT Kharagpur to New York, spent years in enterprise and Amazon-scale systems, and then stepped into a builder phase where product conviction and ownership matter more than looking conventionally impressive.
A kid from India who cleared some of the country's toughest exams (KVPY, IIT JEE), spent 4 years at one of Asia's best engineering schools, then moved to Mumbai and built enterprise systems processing millions of transactions daily. By 25, he'd already shipped production Kafka migrations and led engineering initiatives.
Bet on himself. Left India for a master's at NYU in New York. Graduated and landed at Amazon, where he spent 3+ years building distributed systems at a scale most engineers never see. International marketplace expansion, multi-region AWS, 99.9% uptime. But advertising wasn't the mission.
Left Amazon to build things he actually cares about. Now creating AI-native products (duSraBheja, dataGenie), shipping real client projects (Barbershop booking platform, Kaffa website), and looking for the right team where technical depth meets product passion. Five languages, two countries, three cities, and a portfolio of things he built end-to-end — from architecture to deployment to operations.
Every chapter of Ahmad's career shows the same pattern: arrive somewhere new, learn fast, build real things, ship them. IIT → enterprise systems → Amazon scale → independent builder. The constant is ownership — he doesn't just write code, he ships products. ---
Software Engineer with 6+ years building distributed systems at Amazon and enterprise loyalty platforms. At Amazon, built advertising services that powered international marketplace expansion - Java and Python microservices handling ad delivery across multiple AWS regions at 99.9%+ availability. Currently building two AI-native products: duSraBheja, a personal AI second brain where anything I capture (text, images, audio, PDFs) gets automatically classified, embedded, and made searchable by AI agents through MCP - solving the problem of scattered knowledge across tools. And dataGenie, a conversational data analytics platform that lets non-technical users explore datasets in plain English without writing SQL. IIT Kharagpur and NYU Tandon grad. I work across the full stack and I like owning a product end to end.
Roles across Amazon, Loylty Rewardz, and early systems work before the builder phase.
Formal training that sits underneath the systems and product work.
The stack is broad because the work has been end to end.
Amazon-scale systems, enterprise backend foundations, and then a builder phase where product taste started to matter as much as technical depth.
ML, Deep Learning, Big Data coursework.
Computer Vision, IoT projects.
I like end-to-end ownership, products with a real point of view, and systems where the operational details are part of the product rather than hidden behind it.
It is owning enough of the product to make better decisions: backend systems, AI orchestration, interface quality, deployment, and the narrative layer people actually experience.
The builder phase is as much about operating in public and shipping with conviction as it is about the code itself.
A lot of the product thinking happens while walking near the water or decompressing after a long build day.
Which is probably correct. The home context is part of what keeps the ambition human.