I build things,
break them,
then understand why.
I am Ketan — a full stack engineer, DevOps practitioner, and data scientist based in India. Before I had a job title, I was a co-founder trying to make something from nothing with very limited resources and even more limited sleep.
That experience shaped everything about how I think about software — every decision has a cost, every abstraction needs a reason, and the best architecture is the one that ships and survives contact with reality.
Philosophy
The timeline
Started building
Started with web development as a side interest during college. Built small projects, broke things repeatedly, and got obsessed with understanding how systems actually work under the hood.
Co-founder & CTO
Joined as the founding technical member of a bootstrap startup — effectively a one-person engineering team for the first year. Designed and shipped the entire product: frontend, backend, infrastructure, and CI/CD pipeline. Wore every hat. Learned that the gap between "works on my machine" and "works in production" is where most of the real engineering happens.
Grew the team, stayed technical
As the product found traction, started hiring. Transitioned into a proper CTO role — architecture decisions, code reviews, technical roadmap, and mentoring junior engineers — while still writing production code every day. The experience of growing a technical team from zero taught me more about software quality than any book.
Software developer
Made a deliberate move into a professional services environment to work with larger clients and more complex systems at scale. Currently building here while running the audit side practice and investing spare cycles into personal infrastructure experiments.
What I am focused on
A snapshot of where my time and attention actually go — updated when things change.
Software developer at a service-based org
Working on large-scale client projects, deepening expertise in distributed systems and enterprise Java.
Running cloud audits for Indian startups
Helping early-stage companies identify cost waste and security gaps across AWS, GCP, Azure, and DigitalOcean. Each audit is a fixed-scope, fixed-price engagement.
See audit plans →Investing in a personal GPU setup
The audit income is funding a dedicated inference and training rig. Goal: run experiments locally without cloud GPU costs eating every rupee.
Documenting experiments on the blog
Sharing what works, what does not, and the infrastructure decisions behind both. Mostly DevOps and ML — occasionally CTO war stories.
Read the blog →