Building intelligent retrieval-augmented generation systems and LLM agents that deliver factually grounded, context-aware responses at scale.
I specialize in building Retrieval-Augmented Generation (RAG) systems and intelligent agents that combine LLMs with real-world knowledge bases. I've designed and deployed production-grade RAG applications that enable conversational AI to provide factually accurate, source-grounded responses across various domains.
Beyond RAG development, I have strong expertise in backend engineering, machine learning, and full-stack development. I'm currently pursuing a BS in Computer Science at Air University while continuously building AI projects and pursuing advanced ML certifications.
BS Computer Science
Air University, Islamabad (2023–2027)
Machine Learning Specialization (In Progress)
Coursera / DeepLearning.AI
LLM-powered conversational assistant using RAG for factual, source-grounded religious text queries. Built with LangChain and LangGraph for intelligent agent orchestration.
RESTful API for NFT marketplace with Express.js and MongoDB, handling routing and database integration.
Machine learning system using Random Forest to isolate malicious activity from normal traffic.
Console-based version control simulation using advanced DSA patterns and algorithms.