I'm an Associate Data Scientist at Analytics Vidhya who builds Generative AI and Agentic Systems. I specialize in designing and deploying production-ready AI applications that solve real-world problems through cutting-edge generative AI technologies.

• 🤖 Core Focus: Building Generative AI Solutions & Agentic Systems
• 🔬 Specializations: Multi-Agent Systems, RAG, LLM Fine-tuning, AI Agents
• 🛠️ Tech Stack: LangGraph, CrewAI, Google ADK, Django, FastAPI, LangChain
• ✍️ Technical Writer: 44+ articles on Analytics Vidhya sharing insights on GenAI, AI Agents, Deep Learning and Machine Learning
• 🚀 Building: Production-ready agentic AI systems, conversational AI apps, and RAG-powered solutions

Expertise: Agentic Systems, Multi-Agent Collaboration, Prompt Engineering, RAG (Retrieval-Augmented Generation), Context Engineering, LLM Fine-tuning (PEFT)

Specializations: Natural Language Processing, Computer Vision, GANs, Neural Networks

Vector Databases: Qdrant, Weaviate, ChromaDB

AI Protocols: MCP (Model Context Protocol), A2A (Agent to Agent Protocol)

Monitoring: LangSmith, LangFuse, OpenTelemetry

Data Processing: Pandas, NumPy

AI chatbot with RAG capabilities built using Django, LangGraph, and LangChain. Features document retrieval, multi-LLM support (Gemini/Groq), and a modern web interface.

Implementation of AI guardrails for safe and reliable LLM applications - A DeepLearning.AI course project featuring RAG-powered chatbot with hallucination detection, PII protection, and topic restriction.

A modular implementation of Knowledge Graph–based RAG using Neo4j and LLMs to enable structured, relationship-aware retrieval alongside traditional unstructured text retrieval.

A collection of Jupyter notebooks exploring LangGraph concepts: chatbots, agents, RAG patterns, multi-agent systems, and async workflows.

Learning repository for Google ADK (Agent Development Kit) with 5-day AI agents course, example implementations, and streaming agents using Gemini models.

MCP server providing AI image generation via Google Gemini and weather services for Claude Desktop and MCP-compatible clients.

I write technical articles on Analytics Vidhya covering topics in Generative AI, Machine Learning, AI Agents, and more.

• 🚀 Building AI Agents: Insights from Kaggle's Intensive Program
• 🛡️ Guardrails in LLMs: Building Reliable AI Systems
• 💬 Building a Conversational AI App with Django and LangGraph
• 🤖 What is Gemma 3n and How to Access it?
• 📚 Beginner's Guide to Git
• 🎯 50+ Generative AI Interview Questions

📝 Read all my articles →

Stats: 44+ Articles | 1,163+ Claps | Topics: GenAI, AI Agents, LLMs, ML, Python

• 🤖 Building Agentic Systems: Designing and developing production-ready multi-agent systems with LangGraph, CrewAI, and Google ADK
• 🚀 Generative AI Solutions: Creating end-to-end GenAI applications with RAG, fine-tuning, and advanced prompt engineering
• 🔗 Agent Orchestration: Working on agent workflows, handoffs, and collaboration patterns for complex AI systems
• 🛡️ LLM Safety & Guardrails: Implementing safety measures and guardrails for reliable AI applications
• 📝 Knowledge Sharing: Writing technical content on agentic AI, GenAI solutions, and best practices

I'm always open to discussing Generative AI solutions, agentic systems, collaborations, or sharing insights on building production-ready AI applications!

• 💼 LinkedIn
• 🐦 Twitter/X
• 📧 Email - badrinarayan.muniraja@gmail.com
• 📝 Analytics Vidhya Blog
• 📧 Feel free to reach out via LinkedIn and Gmail