---
title: "SUPRAJA SRI R B - Engineer in AI in Chennai | Tal"
description: "Meet SUPRAJA SRI R B, GenAI Application Engineer | LLMs · LangGraph · Multi-agent orchestration · RAG · FastAPI | Building AI-powered products | AI Engineer @ TCS based in Chennai. AI stack includes claude code, langfuse, and langgraph. Explore public work links including github and leetcode."
image: "https://tal.club/meet/supraja-sri/share-image"
---

# SUPRAJA SRI R B on Tal

## Headline

GenAI Application Engineer \| LLMs · LangGraph · Multi\-agent orchestration · RAG · FastAPI \| Building AI\-powered products \| AI Engineer @ TCS

## About

I build Generative AI products that actually ship\. As an AI Engineer at TCS, I design and develop production\-grade LLM applications — multi\-agent systems, RAG pipelines, vision\-powered AI tools, and full\-stack applications that go from idea to deployed product\. My current focus: Generative AI, Agentic AI, LangGraph multi\-agent architectures, RAG, Google ADK, and MCP — building practical systems that solve real problems, not just demos\. Some things I've built: → House Inspection AI Assistant — LangGraph multi\-agent pipeline with Llama 4 Scout vision model, FastAPI backend, React frontend, deployed on Render \+ Vercel → Meeting Transcription Chatbot — RAG system with Qdrant, HuggingFace embeddings, and Groq for natural language Q&A over meeting content I work across the full AI stack — prompt engineering, vector databases, backend APIs, cloud deployment, and frontend integration\. Fast learner\. Bias for building\. Always experimenting with what's next in AI\. 🔗 GitHub: github\.com/suprajasribalaji

## Location

Chennai

## AI stack

claude code

langfuse

langgraph

lovable

Google ADK

Qdrant

## Work experience

Engineer in AI at Tata Consultancy Services, Oct 2025 \- Present · 10 mos, \- Architected a House Inspection AI Assistant using LangGraph multi\-agent pipeline \(defect classifier \+ report writer nodes\), integrating Groq's Llama 4 Scout vision model for image analysis and Llama 3\.3 70B for report generation\. \- Built a Meeting Transcription Chatbot with end\-to\-end RAG pipeline using LangChain, Qdrant vector database, HuggingFace embeddings, and Groq API for low\-latency LLM inference\. \- Migrated LLM backend from Google Gemini to Groq API across multiple services, implementing optimized rate limiting and async FastAPI endpoints\. \- Designed normalized PostgreSQL schemas with SQLAlchemy ORM, implementing JWT authentication, bcrypt password hashing, and real\-time input validation\. \- Deployed full\-stack AI applications on Render \(backend\) and Vercel \(frontend\) with Firebase storage integration and environment\-based CORS configuration\.

Assistant System Engineer \- Trainee at Tata Consultancy Services, May 2025 \- Present · 1 yr 3 mos, \- Completed foundational training across Linux, Networking, and software engineering practices at TCS\. \- Began transitioning into Generative AI and agentic systems, self\-initiating projects in LangChain, LangGraph, and RAG pipelines\.

Foundations of AI at Edunet Foundation, Apr 2025 \- May 2025 · 2 mos, Hybrid

Intern \- Full stack developer at 5C Network, Oct 2023 \- Apr 2024 · 7 mos, Coimbatore, Tamil Nadu, India, Frontend Development • Improved performance and Maximized UX by fixing bugs and redesigning UI using ReactJS with ViteJS, and React Native\. • Streamlined desktop app navigation by implementing routing with ElectronJS, improving interaction and access across three pages\. • Enhanced user engagement and journey by displaying a welcome modal once per day and optimizing button flows with ReactJS and ViteJS\. • Supported radiologists by adding subtitles modal for easier report management, significantly improving usability and workflow\. • Expanded language accessibility using i18n in ReactJS, broadening the platform’s reach and enhancing user comfort and ease of use\. Backend Development • Implemented RESTful APIs while migrating two microservices from ExpressJS to NestJS across three modules, enhancing functionality and managing dependencies effectively\. • Optimized report generation timelines by redesigning message triggers and extending service hours using SNS, SQS, ExpressJS and MongoDB, ensuring timely email notifications and improved efficiency\.

## Education

Bachelor of Engineering \- BE, Computer Science, Dr\.N\.G\.P\. Institute of Technology\.

HSC, Rajan Matriculation Higher Secondary School

## Public links

- github: https://github\.com/suprajasribalaji
- leetcode: https://leetcode\.com/suprajasri89

[View the original profile](https://tal.club/meet/supraja-sri)

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