Om Thakur builds applied AI and full stack products end to end, from the data layer to the interface, and builds the evaluation that proves they work. Open to full-time roles anywhere in the U.S.
Om Thakur builds software people actually use: retrieval pipelines, agentic workflows, and the full stack products around them. Having completed his Master's in Computer Engineering at NYU (conferred May 2026) and wrapped a year building medical AI at NYU Langone Health, he is looking for his next full-time role.
His work runs from the interface down to the model and back. At NYU Langone he built a clinician-facing retrieval system over 170 clinical documents on a HIPAA-compliant in-house vector store, then built the harness that graded it: ten foundation models across six providers, 1,950 runs scored on latency, cost, faithfulness and citation quality. It caught silent failures in citation grounding that no demo would have surfaced.
"Anyone can demo a model. The work is proving it still holds on the thousandth query."
That belief is now packaged and public. benchtrace on PyPI measures whether one model is actually better than another and refuses to name a winner when the evidence does not support one. agentcassette on npm records an agent run once so a test suite stops paying an API bill to learn the same thing twice.
He takes projects end to end, from a vague idea or a detailed spec through design, testing and production-hardening, solo or on a team, and has worked with clients from first ideation through shifting requirements. The same year at Langone he stood up HPC pipelines moving 50+ terabytes of clinical sequencing data across NVIDIA A100 GPUs.
Earlier, at 4iBiz, he shipped SaaS to more than 20,000 users, cut dashboard latency in half across a thousand gyms, and delivered 18 production features on an eight-engineer team. Underneath all of it sits a systems habit: a message queue written in Rust, a consensus store machine-checked in TLA+. Understanding how things fail is what makes the rest trustworthy. Off the clock, he is found photographing the city on a 35mm, on the cricket pitch, or mentoring students at NYU Tandon.