Generative AI Engineer with less than a year in LLMs and RAG frameworks
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I am Computer Science graduate with expertise in Python, Machine Learning, Deep Learning, and Generative AI, complemented by practical experience in developing AI-based solutions and intelligent systems. Skilled in problem-solving, software development, and collaborating on innovative projects, with a keen interest in LLMS, RAG pipelines, AI agents, and modern AI application development.
FAST - National University of Computer and Emerging Sciences
Bachelor of Science · Computer Science
N/A – June 30, 2024
Aga Khan Higher Secondary School Gahkuch
F.Sc · Physics, Chemistry, Mathematics
N/A – Present
SmartStudy Companion using Knowledge Graph and RAG framework
June 1, 2024 – Present
The SmartStudy Companion is an AI-driven application that personalizes programming education using Knowledge graph and RAG. It adapts learning paths based on user skills, offers contextual chatbot assistance and track progress with adaptive quizzes.
Handwritten Character Recognition for Medical Report Processing
January 1, 2023 – June 1, 2023
Developed a deep learning-based system for handwritten medical report character recognition using CNNs, RNNs, Transformers, and hybrid architectures. Evaluated models on IAM and PEIR datasets to enhance accuracy, noise robustness, and support automated report processing
Agent RAG system to assist student prepare for quizzes
January 1, 2023 – June 1, 2023
Multi Agent RAG system to assist student prepare for quiz via an AI quiz generation, summarize the PDF's especially for FAST students by training on the Fast NUCES Past Papers and geeks for geeks site.
Agent RAG CaPix: captioning using CLIP + LLM
January 1, 2023 – June 1, 2023
Developed an AI-powered image captioning system using CLIP for visual feature extraction and an LLM for generating accurate, human-like captions. The system combines computer vision and natural language processing to produce meaningful descriptions of image content.
Cricket Match Simulator – Programming Fundamentals Project
January 1, 2023 – June 1, 2023
Built a console-based cricket match simulator using arrays, randomization, and file handling to track real-time scores, player stats, and match outcomes with dynamic gameplay features.
Automated Exam Timetable Generation using Genetic Algorithm
January 1, 2023 – June 1, 2023
Developed a Genetic Algorithm to generate conflict-free university exam timetables, satisfying hard and soft constraints and automated scheduling from Excel data with real-time fitness evaluation and visualized outputs.
AWS Cloud Quest: Cloud Practitioner
Amazon Web Services
May 1, 2026 – Present
Implementing AI solutions in Business
DataCamp
April 1, 2024 – Present
Introduction to Python
DataCamp
February 1, 2024 – Present
Intermediate & Advance Python
DataCamp
February 1, 2024 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from handwritten character recognition to multi-agent RAG systems and genetic algorithms, shows a broad interest in AI applications. The focus on Generative AI and RAG pipelines aligns well with the target role of a Generative AI Engineer. However, all projects are academic, which might indicate a need for adaptation to industry-specific workflows and collaborative environments. The candidate's participation in open-source contributions (Mozilla Common Voice) and seminars suggests a proactive and community-oriented approach, which is a positive indicator for cultural fit.
Soft Skills & Operational Fit
The candidate's resume highlights 'Communication skills, Team work, Adaptability' as professional skills. Project descriptions suggest an ability to work on complex problems and integrate various AI techniques. The academic nature of all projects, however, means there is no direct evidence of operational fit within a professional team or handling production-level systems. The candidate's involvement in Mozilla Common Voice (Urdu) and attending seminars indicates a collaborative and learning-oriented mindset.