I’m a Senior Software Development Engineer with over 5+ years of experience specializing in highly scalable cloud infrastructure, full-stack web applications, and AI integrations. I currently work at Aereo, where I architect complex geospatial analytics pipelines, port massive AWS workloads to Kubernetes, and build agentic AI chatbots using RAG and LangGraph.

When I'm not bringing “it works on my machine” into production, I'm relentlessly optimizing CI/CD workflows, cutting cloud costs by 90%, or experimenting with LLMs.

• 🌍 Based in Bengaluru, India
• 🤝 Open to collaborating on Open Source, ML ops, and scalable system design
• 📜 Patent Holder: Co-invented a core architecture system for a drone-based geospatial analytics platform.

If you want to see how I write code and design systems at scale, check out my flagship Atlas Platform—an enterprise-grade modular monolith built to handle heavy data processing, decoupled background jobs, and real-time event streams.

A high-performance React/Vite frontend orchestrating state across multiple micro-feature domains. Built for scale using aggressive React Query caching to minimize network waterfalls, fine-grained domain state management (MobX) to prevent UI blocking, and Server-Sent Events (SSE) for lightning-fast real-time synchronization. Capable of smoothly rendering extremely heavy, complex datasets directly in the DOM.

An event-driven modular monolithic architecture orchestrating 10+ Python/Django micro-apps. Engineered for high concurrency by aggressively offloading heavy compute tasks (like agentic LLM inference and massive batch processing) to a Celery/Redis worker farm. Features an integrated Daphne/Channels layer for low-latency websockets and is deployed entirely on Kubernetes (K8s) using custom Helm charts for seamless auto-scaling.

JavaScript	TypeScript	Python	React	Django	FastAPI
PostgreSQL	Redis	AWS	Docker	Kubernetes	Terraform

AI & Machine Learning: PyTorch, FastAI, LangChain, LangGraph, Retrieval-Augmented Generation (RAG)