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jairamshegde/README.md

Hi πŸ‘‹, I'm Jairam Hegde

Lead AI Engineer

5+ years in engineering | Shipping agentic AI in enterprise & SaaS | Systems thinker

πŸ‘¨β€πŸ’» About Me

Lead AI Engineer. I take ambiguous AI ideas and turn them into production systems β€” agentic RAG, multi-agent orchestration, regulated enterprise.

Currently focusing on:

  • πŸ—οΈ Enterprise RAG Systems - Advanced contextual retrieval at scale
  • 🎯 Context & Prompt Engineering - Optimizing LLM performance
  • πŸ“Š MLOps - MLflow integration for monitoring and observability
  • πŸ€– Agentic AI - Designing intelligent automation workflows

πŸš€ What I Bring to the Table

  • βœ… Production Experience: Deployed GenAI applications serving enterprise users
  • βœ… Full-Stack AI: From data pipelines to LLM integration to deployment
  • βœ… Best Practices: MLflow for tracking, context engineering for accuracy
  • βœ… Modern Tools: Claude Code, LangChain, FastAPI, Azure AI, Vector DBs

πŸ’‘ Key Areas of Expertise


RAG Architecture
Advanced contextual retrieval
Enterprise-scale systems
Vector database optimization

Prompt Engineering
Context optimization
Chain-of-thought techniques
Production LLM performance

LLM Applications
Full-stack AI development
API integration
Production deployment

Agentic Workflows
Intelligent automation
Multi-agent systems
LangGraph orchestration

MLOps & Observability
MLflow tracking
Model monitoring
Performance optimization

Cloud Deployment
Azure AI services
Scalable architectures
Docker containerization

πŸ› οΈ Tech Stack

Category Tool Tool Tool Tool
🧠 AI & LLMs
ChatGPT

Claude

Claude Code

Antigravity
🧩 LLM & Web Frameworks
LangChain

LangGraph

PocketFlow

FastAPI
πŸ€– ML & Deep Learning
PyTorch

scikit-learn

NumPy

MLflow
πŸ—„οΈ Data & Vector Stores
PostgreSQL

Qdrant
☁️ Cloud & Infra
Azure

Azure AI Foundry

Docker
πŸ› οΈ Dev & Tooling
Git

Python

Hugging Face

Ollama

🎯 Current Learning Journey

  • Building advanced agentic systems with Claude Code and custom skills
  • Enterprise automation patterns (and knowing when NOT to use agents!)
  • Voice-enabled GenAI applications for productivity
  • MLOps best practices for production LLM applications

πŸ’¬ Let's Talk About

  • 🎨 Advanced Prompt Engineering techniques
  • πŸ—οΈ RAG system design and optimization
  • πŸ€– LLM-powered learning and productivity tools
  • πŸ“Š Deploying AI at enterprise scale

πŸ“« Get in Touch

⚑ Building exciting tools and application using AI Engineering and GenAI

profile views

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  1. Ai-Agents-Reads Ai-Agents-Reads Public

    My reading list of AI Agents

  2. micro_chat_gpt micro_chat_gpt Public

    My version of building fully functional conversational AI.

    HTML

  3. My-Awesome-RAG-Reads My-Awesome-RAG-Reads Public

    This is my curated repo regarding Retrieval Augmented Generation(RAG).

  4. naupe naupe Public

    Simplest payroll micro-saas for the team with less than 10 people. Thats why the name!