I am a Python developer focused on Backend Engineering and AI. I build reliable APIs using FastAPI, manage data with PostgreSQL, and build tools that use AI to solve real problems

Domain	Stack
Backend Engineering
Database & ORM
Applied AI

Autonomous Multi-Agent Intelligence Gatherer An autonomous system that iteratively researches a topic, evaluates its own findings, and generates a fully cited, hallucination-free executive summary.

• Core Problem: Deep-dive research is time-consuming, and standard LLMs frequently hallucinate facts or invent citations when asked to write comprehensive reports.
• Solution: Orchestrated a multi-node state graph using LangGraph with a "Plan-and-Solve" architecture. It utilizes Planner, Worker, and Critic agents to dynamically scrape the web and execute ephemeral RAG pipelines, forcing the LLM to ground its output strictly in retrieved data.
• Key Tech: Python, LangGraph, FastAPI, Streamlit,FAISS, Docker.

Automated RAG-Based Screening System An intelligent document-parsing and evaluation API that deterministically scores candidates against job descriptions.

• Core Problem: Manual resume screening is slow, highly subjective, and standard keyword parsers often fail to understand true technical context.
• Solution: Architected a Retrieval-Augmented Generation (RAG) pipeline utilizing ChromaDB for semantic search, and implemented Instructor/Pydantic to force the LLM into outputting strict, hallucination-free JSON decisions (Match/Reject).
• Key Tech: Python, FastAPI, ChromaDB, Groq LLM, RAG, Streamlit.

High-Concurrency Ticketing System A robust booking API designed to handle race conditions during high-demand events.

• Core Problem: Preventing "double-booking" when thousands of users hit the endpoint simultaneously.
• Solution: Implemented Atomic Transactions and database locking strategies to guarantee inventory consistency.
• Key Tech: FastAPI, PostgreSQL, JWT Authentication, Docker Compose.