AI Engineer • Agentic AI • RAG Systems • Backend Development

Building intelligent systems that can reason, retrieve information, use tools, and solve real-world problems.

I am currently focused on building AI applications powered by Large Language Models, Agentic Workflows, and Retrieval-Augmented Generation (RAG).

My interests include:

• Agentic AI Systems
• Multi-Agent Workflows
• LangGraph
• Retrieval-Augmented Generation (RAG)
• Voice AI Agents
• AI Evaluation & Guardrails
• Backend Engineering
• AI Infrastructure

AI Engineering

Python • LangChain • LangGraph • OpenAI • Gemini • MCP • Vector Databases • RAG • Prompt Engineering

Backend

Node.js • Express.js • FastAPI • MongoDB • MySQL • PostgreSQL

Cloud & DevOps

Docker • Linux • GitHub Actions • Google Cloud Run • DigitalOcean

Frontend

React • Next.js • Tailwind CSS

Production-grade Agentic RAG system for analyzing financial reports and enterprise documents. Features hybrid retrieval, reranking, financial reasoning workflows, citation-based responses, and document intelligence pipelines.

Key Concepts: RAG, Hybrid Search, Vector Databases, Reranking, Agentic Workflows, FastAPI, LangGraph

Multi-agent research platform that autonomously plans, researches, critiques, and synthesizes information into structured reports. Built around planner agents, reflection loops, memory, tool orchestration, and workflow-based reasoning.

Key Concepts: Multi-Agent Systems, LangGraph, Planner Agent, Reflection, HITL, State Management, Memory, Tool Calling, Observability

Agentic AI assistant that helps students prepare for placements through personalized roadmaps, interview preparation, skill-gap analysis, mock interview workflows, and intelligent resource retrieval.

Key Concepts: Agentic AI, RAG, Planning Workflows, Structured Outputs, User Memory, LLM Applications

Deep learning application for detecting AI-generated images using computer vision models. Provides confidence-based classification between real and synthetic images through an interactive web interface.

Key Concepts: Computer Vision, Deep Learning, PyTorch, CNNs, FastAPI, Model Deployment

Currently exploring:

• Advanced RAG Architectures
• Agent Memory Systems
• Multi-Agent Orchestration
• AI System Design
• LLM Evaluation
• Production AI Deployment

Portfolio: om-wagchavare.vercel.app

LinkedIn: linkedin.com/in/om-waghchavare-883ba9286

LeetCode: leetcode.com/u/om_waghchavare

Email: waghchavareom@gmail.com

"I enjoy building AI systems that don't just generate text, but can reason, retrieve knowledge, use tools, and take actions."