EngineeringEngineering thethe systemssystems behindbehind intelligentintelligent software.software.
I build intelligent systems by combining backend engineering with generative AI, agentic workflows, and production-minded software architecture — not chatbot wrappers, complete workflows around the model.
FromFrom graduationgraduation toto whatever'swhatever's next.next.
Not a resume. A route — each stop a checkpoint, the last one not reached yet.
Graduated — VIT Chennai
B.Tech in Computer Science, specialization in AI & Robotics. GPA 9.11. Four years of CS fundamentals, machine learning, and robotics — the base camp everything else launches from.
Research Intern — VIT
Fine-tuned an EfficientNetV2B0 model for rice leaf disease recognition and co-authored a published IEEE paper on the results. First real exposure to rigorous ML evaluation.
Read the IEEE paper →Software Development Intern — LogicalAt
Applied Linear Regression, KNN, Ridge, Lasso, and MultiOutput Regressors to industrial color manufacturing, with PCA-driven feature engineering against real operational constraints.
Specialist Programmer — Infosys
Extending a telecom order-fallout automation platform, then architecting a distributed multi-agent A2A system — LangGraph, RAG, ChromaDB, human-in-the-loop execution.
Something Big
There's more I want to build, more I want to learn, and somewhere bigger I want to be.
Built.Built. Broken.Broken. Learned.Learned. Rebuilt.Rebuilt.
A growing collection of things I've built — each one teaching me something I didn't know before.
TheThe toolstools behindbehind thethe thingsthings II build.build.
Backend & APIs
The systems layer behind the intelligence.
Infrastructure & Engineering
How ideas become reliable, deployable systems.
Frontend
Enough to take an idea all the way to the interface.
AI Systems
Where models become useful software.
ML Foundations
The foundation underneath the AI layer.
TheThe samesame process,process, everyevery time.time.
I don't just learn how a technology works. I want to understand the problem it solves, what happens underneath, and why I'd choose it over the alternatives.
I care about what happens beyond the happy path. Authentication, async processing, caching, observability, and failure handling aren't extras bolted on at the end — they're part of the system from the beginning.
Questions I ask before I trust a tool
- 01What problem does it actually solve?
- 02What's happening underneath?
- 03What alternatives exist?
- 04What are the trade-offs?
- 05How does it behave under real-world load?
- 06What happens when things go wrong at 3am?