Generative AI Engineer with less than a year in AI/ML & NLP
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As a Computer Science graduate from FAST-NUCES and passionate AI/ML Engineer specializing in Gen-AI and NLP, I bring hands-on expertise in orchestrating multi-agent systems and deploying full-stack intelligent applications. With technical knowledge in frameworks like LangChain, LangGraph, Docker, and FastAPI, I am dedicated to architecting robust, scalable, and user-centric AI solutions that solve complex real-world problems.
FAST National University of Computer and Emerging Sciences (NUCES)
Bachelor of Science · Computer Science
N/A – June 30, 2026
FAST NUCES
Artificial Intelligence Lab Demonstrator
January 1, 2025 – April 1, 2025
Islamabad, Islamabad Capital Territory, Pakistan
Final Year Project - Agentic AI-Powered Urdu Voice Ordering Assistant (SmartOrder)
January 1, 2025 – June 1, 2026
Developed a voice-based food ordering and reservation system supporting Urdu, English, and code-mixed speech. Designed end-to-end architecture including ASR, NLU, multiple agents routing through LangGraph, and backend services deployed on Azure with Docker container images.
Cloud-Native Web Application Deployment on AWS
January 1, 2025 – December 31, 2025
Deployed a Dockerized full-stack application leveraging AWS for scalable cloud hosting and infrastructure management.
DocuMind: AI Proposal Engine with RAG Architecture
January 1, 2025 – December 31, 2025
Developed a Dockerized full-stack agentic system (FastAPI, Streamlit) using LangChain and ChromaDB to automate B2B proposal generation via semantic retrieval.
Council Mode: Multi-Agent RAG Framework with Skeptic-Driven Validation
January 1, 2025 – December 31, 2025
Architected a heterogeneous LLM ensemble (LangGraph, AutoGen) featuring a Skeptic-driven validation loop, intelligent triage, and iterative re-retrieval, reducing hallucinations by 35%.
AI & Machine Learning Internship
DevelopersHub Corporation
November 1, 2025 – Present
Generative AI Internship & Training Program
Arch Technologies
October 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest and practical application in cutting-edge AI fields, particularly Generative AI and multi-agent systems. The diversity of projects, from voice assistants to proposal engines and RAG frameworks, shows a broad technical curiosity and willingness to tackle different challenges. The target role of Generative AI Engineer aligns well with the candidate's project focus and stated career aspirations. The candidate is still pursuing a bachelor's degree, which might indicate a need for mentorship and structured guidance in a professional setting.
Soft Skills & Operational Fit
The candidate's experience as an AI Lab Demonstrator suggests an ability to communicate technical concepts and assist others, which is valuable for team collaboration. Project descriptions indicate a problem-solving mindset and an interest in reducing AI limitations (e.g., hallucination reduction). The team lead role points to organizational and leadership potential.