The Beginning
My professional software engineering journey started with learning HTML, CSS, and JavaScript from scratch. This phase built the foundation that shaped everything that followed.

I build software that solves real-world problems — from healthcare platforms and enterprise automation to scalable data processing systems.
My Computer Science degree introduced me to software fundamentals, but my real engineering journey began when I joined the industry and started solving problems for real users.
Building enterprise ETL workflows with Apache Airflow that turn messy payer data into decisions for US pharma teams.
I don't identify with one layer of the stack. I identify with the outcome — reliable software that people actually use.
React apps with real state discipline — reusable components, accessible flows, and interfaces that stay fast under real data.
A milestone-based path of fast learning, real projects, and steady growth into larger engineering challenges.
Different domains, same instinct: build something reliable, ship it, then make it faster and safer with every iteration.
Electronic Hospital Management System
A hospital-grade management platform built on top of ERPNext Healthcare. Clinicians, front-desk staff and administrators all live in the same system — with workflows tailored to each.
Enterprise Server Fleet Management
A control plane for Cisco Integrated Management Controllers — monitoring, inventory, power, firmware and configuration across a fleet of enterprise servers.
Pharmaceutical Market Access Platform · Current
A platform that helps US pharmaceutical teams understand insurance coverage, plan drug launches, and answer 'which patients can actually get this drug?' with data instead of guesswork.
Next mission · In progress
The next build is already in orbit. New case studies land here as soon as they ship — same thesis, new problem.
I don't list technologies I've read about. I list the ones I've shipped with.
These aren't buzzwords. They're the operating principles that show up in every commit.
I don't wait to be told what to learn. New tech shows up, I try it, break it, use it.
I don't hand off. If it broke on my watch, it's mine to fix — and my job to make sure it doesn't happen twice.
I move across frontend, backend and data without ceremony. The problem picks the layer, not my comfort zone.
I've built for operators, clinicians and analysts. I know that boring reliability beats flashy features.
If I do it twice, I script it. If we do it as a team, I turn it into a tool.
AI is a teammate in my loop — for prototyping, refactoring, learning new stacks faster than I could alone.
Every review is a chance to be less wrong tomorrow. I chase that on purpose.
I care about users, not just tickets. I want to see the thing I built help someone do their job better.
I'm open to roles where I can go deep on a real product, work with a team that cares about craft, and keep learning at the pace I'm used to. If that sounds like your team — say hi.