I architect systems
that scale, learn
and perform.
From real-time enterprise monitoring platforms to AI-powered analytics, I turn complex business problems into scalable software systems.
Building with large language models
Not just calling an API — designing the retrieval systems, agent workflows and pipelines that make LLMs useful in production.
What you might be dealing with
Most engineering challenges trace back to a handful of root causes.
Your platform can't keep up with growth
Systems built for 100 users buckle at 10,000. You need architecture that scales horizontally without a full rewrite.
Data flows but insights arrive too late
Events are streaming but nothing is connected. By the time you spot a problem, users have already noticed it.
AI feels like a distant goal, not a tool
Everyone is talking about ML and LLMs, but integrating intelligence into a production system is a different discipline.
Technical debt is slowing every delivery
The codebase has outgrown its architecture. Teams ship more bugs than features because the foundations aren't solid.
Three ways to work together
Full-Stack Architecture
End-to-end system design — React frontends to microservices to data layers. Designed for maintainability and growth, not just the MVP.
Platform Engineering
Distributed systems built for real throughput — Kafka event pipelines, WebSocket real-time layers, Python workers that handle 100K+ events per second.
AI / ML Integration
Embedding intelligence into production — RAG pipelines, LangChain agents, anomaly detection and natural-language interfaces built on your existing data.
Three projects, three problems solved
10+ years, four companies
R&D Lead Software Engineer
- —Architected a MERN + Python monitoring platform serving 10,000+ concurrent users at 99.9% uptime
- —Designed Node.js microservices (Express/NestJS) handling 1M+ API requests/day with event-driven flows via Kafka and RabbitMQ
- —Built FastAPI workers processing 100K+ events/second with ML-based anomaly detection; optimized MongoDB pipelines cutting query time by 70%
Senior Software Engineer
- —Architected a MERN e-commerce platform processing 50,000+ daily transactions with SSR Next.js 14, improving SEO by 40%
- —Reduced API latency to sub-200ms through Redis caching; achieved 95+ Lighthouse scores and 85% test coverage
- —Led a TypeScript migration cutting runtime errors by 40%; implemented an API Gateway with the BFF pattern
Senior Associate
- —Designed an enterprise multi-tenant SaaS platform serving 50,000+ users with MERN + Python
- —Architected Express REST APIs with multi-tenancy support; optimized MongoDB queries cutting response time by 60%
- —Mentored 5+ engineers on React, Node.js and MongoDB best practices; led technical interviews
Associate / Programmer Analyst
- —Led migration of 15+ legacy .NET applications to a modern MERN stack architecture
- —Architected React financial systems serving 5,000+ users; improved performance by 50% across React Native mobile apps
- —Managed 25+ production servers with zero-downtime blue-green deployments; established CI/CD with Jenkins and ELK monitoring
From problem to production
Understand
Start with the business constraint — not the technical wish list. What's the actual bottleneck? What does success look like?
Architect
Shape data flow, service boundaries and failure modes before the first line of code is written.
Build
Clean, testable, maintainable code. No clever tricks that only I can read in six months.
Validate
Load-test, monitor, harden. Keep it reliable at 3am — not just at demo time.
Building at the intersection of scale and intelligence.
I'm a Full-Stack Architect with 10+ years building enterprise systems that handle real load — 10,000+ concurrent users, 100K+ events per second, 1M+ API calls a day.
My work spans the full stack: React frontends, Node.js microservices, Python processing workers, Kafka event pipelines, and AI/ML layers that make systems smarter over time.
Based in Chennai, India. Currently R&D Lead at Visics India ATG, architecting a MERN + Python monitoring platform for enterprise operations.
Get in touch“Scale isn't something you bolt on — it's something you think through on day one.”
Every system I've shipped was designed for load from the first architecture decision.
“AI isn't a layer you add later. I architect it in from the start.”
LLMs, RAG pipelines, and intelligent agents work best when the data model is built around them.
“I measure success in uptime and outcomes, not features shipped.”
99.9% platform uptime and 1M+ daily API calls aren't accidents — they're decisions made early.
Ready to build
something together?
Whether you need a full-stack architect, a platform review, or help integrating AI — let's talk.