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Aman00240/README.md

Hi, I'm Aman ๐Ÿ‘‹

Python Backend Developer & AI Engineer

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


๐Ÿ› ๏ธ Technical Skills

Domain Stack
Backend Engineering FastAPI Python Docker
Database & ORM PostgreSQL SQLAlchemy
Applied AI Groq ChromaDB RAG

๐Ÿš€ Featured Engineering Projects

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.

Structured Data Extraction Pipeline A vision-based tool that transforms unstructured receipt images data into strict, validated JSON.

  • Core Problem: Manual data entry from receipts is time-consuming and prone to typos/human error.
  • Solution: Built an intelligent extraction pipeline using Llama Vision to read messy images and Pydantic to enforce strict accuracy (ensuring data format is correct).
  • Key Tech: Llama Vision (via Groq), Python, Pydantic.

Current Research & Development

I am currently transitioning from standard RAG pipelines to building autonomous, stateful AI agents.

  • Active Experiment: Developing a multi-tool autonomous agent using LangGraph, Python (AsyncIO), and local SQLite persistence.
  • Goal: Building an end-to-end "Coder Agent" capable of dynamic web searching, real-time web scraping, and local file system execution.

๐Ÿ“ซ Connect

Pinned Loading

  1. RESUME_SCANNER RESUME_SCANNER Public

    An AI-powered Resume Screening API built with FastAPI, Groq (Llama 3), and ChromaDB. It analyzes resumes, detect role mismatches, and rank candidates with strict recruiter logic.

    Python

  2. Research-Assistant Research-Assistant Public

    An AI-powered research assistant that automates deep-dive information gathering. Orchestrates Planner, Worker, and Critic agents to produce data-driven, fully cited executive briefs.

    Python

  3. BOOKFAST BOOKFAST Public

    BookFast is a high-performance, asynchronous REST API for event ticketing, built with FastAPI and PostgreSQL.

    Python

  4. RECEIPT-PARSER RECEIPT-PARSER Public

    Extract structured JSON data from receipt images using llama-4-scout (via Groq). Built with Python, FastAPI, Docker, and Streamlit.

    Python

  5. AI-Engineering-Roadmap AI-Engineering-Roadmap Public

    Zero to AI Engineer: A structured 6-month roadmap. Building production-ready AI applications using Python, LangChain, and CrewAI

    Python