AI Automation & Fullstack Engineer
LLM & Voice Agents · Cloud Architecture · Video Streaming · DevOps
I build AI-powered products end to end — from real-time LLM voice agents and automation pipelines to cloud-native platforms on AWS. My work spans Django & DRF backends, React / Next.js frontends, video streaming (HLS/DASH), OCR and large-scale scraping, and production DevOps with Docker, ECS Fargate, and CI/CD. I care about clean architecture and shipping products that actually make it to production.
5+
Projects
18+
Months Exp
10+
Technologies
Looking for someone who can build scalable, AI-powered products?
From real-time LLM voice agents to cloud-native platforms on AWS — let's build together.
Let's build togetherProduction website and LMS for a coding & AI training institute. SEO/GEO optimized with structured data, dynamic sitemap, and LLM crawler support.
Full-featured learning management system with video transcoding, mentor scheduling, job board, code compiler, and adaptive streaming (HLS/DASH). Deployed on AWS ECS Fargate with CI/CD.
Discover and connect with potential business leads using reverse-engineered Google Maps API with configurable search radius and pagination.
A full-stack AI-powered outbound calling CRM for managing leads, campaigns, live voice conversations, transcripts, and real-time dashboards.
A match-3 puzzle game built as both a web app and a React Native mobile app with level progression and confetti animations.
A multifunctional media platform with contract analysis, progress tracking, and media inspection tools built as a monorepo.
Pharmacy e-commerce with cart, order flow, and Telegram bot integration for automatic delivery dispatch.
Fast, minimal pastebin alternative deployed on Cloudflare Workers edge network.
A macOS desktop UI clone built with React, featuring window management and dock animations.
Clean, responsive news aggregator with category filtering and real-time article fetching.
A visually rich image gallery with smooth layouts and responsive grid design.
Poster aggregation from Netflix, Prime, Hotstar with DASH stream parsing and quality selection.
Thoughts on tech, projects, and learnings.
A ground-up tour of the real system that dials a phone, streams audio into an LLM, talks back in real time, and logs everything to a live dashboard — telephony, media bridging, VAD, barge-in, and the state machine that ties it together.
A practical walkthrough of how we connected telephony, streaming audio, and an LLM-based voice agent for live outbound calls.
How we pushed live call status, transcripts, and dispositions to the frontend without polling the server.
How we structured the backend so telephony events, AI sessions, transcripts, and background tasks all work together cleanly.
Zustand offers simpler state management without boilerplate. Here's my experience migrating a production app.
How I built a video transcoding pipeline that converts uploads into HLS/DASH streams automatically.
Practical guide to adding AI features to your fullstack apps using OpenAI API and prompt engineering.