Work

Case studies in AI, cloud migration and platforms.

Outcomes first, then the architecture behind them. A cross-section of what I’ve built and led, from a founder’s bet to platform-scale infrastructure. Each one links to a write-up of how it was done and what I’d keep.

01Co-founder · AI product

FinMoon AI

Busy Indian professionals make tax, insurance, loan and investment decisions alone, against products built to confuse.

2,000+

applications, and FinMoon AI was selected for the Google for Startups Hub at T-Hub, Hyderabad

200 users in the first beta

An AI assistant that runs the expert decision process, personalised to each user’s finances. It compares options, surfaces risks and hidden costs, and recommends next steps. Not a generic tip; a structured process.

LLMs
Agentic workflows
Product strategy

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02Lead DevOps Engineer · Cloud platform

Cloud Infrastructure Migration

Legacy systems had to move to the cloud without betting the business on a weekend cutover.

40%

lower infrastructure cost after moving legacy systems to Google Cloud

Moved legacy systems onto Google Cloud Platform with infrastructure as code and automated delivery, improving scalability while cutting the bill.

Google Cloud
Kubernetes
Terraform
CI/CD

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03Principal Software Engineer · Distributed systems

Microservices Platform

A high-traffic product needed an architecture that keeps serving users while parts of it fail.

99.9%

uptime, a budget of about 43 minutes of downtime a month

Millions of users served

Designed and implemented a service architecture for a high-traffic product, with caching, containerised deploys and orchestration built for failure.

Spring Boot
Docker
Kubernetes
Redis

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04Senior Developer · Product engineering

Enterprise MVP

An enterprise client wanted a fast demo that could also become the real system if it worked.

0 → 1

led end to end, from first requirements to launch

Led a complete MVP for an enterprise client, with an architecture designed to survive success rather than be rewritten after it.

Angular
Spring Boot
PostgreSQL
Docker

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Track record

The numbers behind it.

years building and running production software: 10+
infrastructure cost cut in a legacy-to-GCP migration: 40%
uptime on a microservices platform serving millions: 99.9%
applicants; FinMoon AI selected for Google for Startups Hub at T-Hub, Hyderabad: 2,000+

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