AI Systems & Backend Engineer · Bengaluru
My main tech stack is Python and TypeScript , with FastAPI and Next.js for building scalable full-stack applications .
I build AI Agents systems using LangChain and LangGraph , and deploy real-time voice agents with Pipecat .
For infrastructure, I use AWS and Docker , and manage data with Neo4j , PostgreSQL , and Redis .
Oct 2025 — Present · Remote
Architected an extensive AI agent orchestration platform (meetchamp.in/ai) where founders upload pitch data to interact with simulated AI investor personas, organically acquiring and successfully serving 200 users on launch day.
Engineered a "second brain" system utilizing non-context graphs, autonomous learning modules, and dynamic persona creation to deeply personalize agent behaviors and knowledge retrieval.
Served as one of three core team members, taking ownership of the majority of the backend architecture, AWS infrastructure (ALB, SQS), and production deployments.
A look back at my work. Selected archives showcasing projects across AI, voice, and full-stack.
Autonomous A2A Networking Platform
Building an Agent-to-Agent (A2A) network where real professionals can create their AI digital twin in under 2 minutes to autonomously network and evaluate synergies on their behalf. Integrated seamless Telegram connectivity for agent interaction.
Universal Smart Device Enabler
Engineered a custom hardware-software bridge using ESP32 microcontrollers that can retrofit any standard physical appliance into an intelligent, AI-controlled IoT device. Near-instant execution (~530ms latency).
No-Code AI Agent Platform
Full-stack platform allowing users to create custom AI assistants, connect them to structured data, and deploy them via an embeddable iframe widget with real-time WebSocket communication. Dynamic Tool Generation pipeline using LLM structured outputs.
Automate Website Testing with AI
AI-powered web testing automation tool using Playwright and LLMs to generate and execute test cases from natural language.
Authoring paper on "Dynamic Tool Generation" introducing a novel pipeline that autonomously converts raw data into executable LLM tools, validated to cut development time by ~90%.
Developed and deployed 10+ freelance projects end-to-end — from initial client consultation and system design to production deployment and ongoing maintenance, taking full ownership of the entire development lifecycle across diverse tech stacks.
Sir M. Visvesvaraya Institute of Technology, Bengaluru
Expected Aug 2027 · CGPA: 8.5/10
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AI, voice agents & full-stack engineering
I Tried Running a Local LLM on My Android. Here's What I Found.
Llama.cpp was unusable. Google AI Edge Gallery was surprisingly good. And now I know exactly why — and what to build next.
Your Prompts Are Terrible Because You're Typing Them
Most people blame the model. The problem is always the prompt. Here's how to fix yours.
Kitchen Surveillance with OpenClaw: Person Detection Under 50MB RAM
How I built a real-time kitchen surveillance agent on a Redmi Note 7 Pro using MobileNet-SSD, OpenCV, and TFLite — detecting people under 50MB RAM and sending Telegram photo alerts.
