AI Engineer with less than a year in Generative AI & LLMs
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Software Engineering student with hands-on experience in Generative AI, Large Language Models (LLMs), and Agentic AI systems. Skilled in building RAG-based chatbots, multi-agent systems, and AI automation pipelines powered by LLM orchestration and autonomous workflows. Focused on building scalable AI systems that enhance efficiency, decision-making, and real-world automation.
University of Engineering & Technology, Taxila
BSc. Software Engineering · Software Engineering
August 1, 2022 – June 30, 2026
Kangaroo Ventures
Data Science Intern
August 1, 2025 – September 30, 2025
United States
Leverify Quest
Data Analyst Intern
September 1, 2024 – October 31, 2024
Pakistan
Multi-Agent Research System
January 1, 2023 – Present
Built an automated multi-agent pipeline using LangChain, Gemini 2.5 Flash, and Python, integrating the Tavily API and BeautifulSoup for precise web searching and data extraction. Developed a responsive Streamlit platform to orchestrate a 4-stage workflow (Search, Read, Write, Critic), efficiently parsing up to 3,000 characters per source to generate and autonomously evaluate structured reports.
View ProjectAI-SmartNaggar
January 1, 2023 – Present
Built AI SmartNaggar, a multi-modal AI-powered civic issue reporting system enabling citizens to report urban problems via text, image, and voice, using MobileNetV2 (PyTorch) for image classification, Whisper for speech-to-text, and TF-IDF + Logistic Regression for NLP-based complaint categorization. Developed a Streamlit + Supabase platform with Folium geolocation mapping that automatically routes complaints to relevant municipal departments, enabling real-time tracking, analytics, and faster resolution of civic issues.
AI-Powered Cheating Detection System
January 1, 2023 – Present
Built a real-time computer vision system using Python, OpenCV, and YOLO-based object detection to monitor exam environments and detect suspicious behaviors. Integrated gaze tracking, face detection, and object detection, achieving 89% detection accuracy on a labeled dataset of 10k images.
NLP-RAG Systems & AI Agents
Awfera
April 1, 2026 – Present
Google AI Professional Certificate
April 1, 2026 – Present
IBM Data Science Professional Certificate
IBM
June 1, 2025 – Present
Career Essentials in Software Development
Microsoft & LinkedIn
November 1, 2024 – Present
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong interest in applying AI to real-world problems, aligning well with an innovative and impact-driven culture. The diversity of projects (computer vision, NLP, multi-agent systems) indicates a broad technical curiosity. However, the limited professional experience and focus on personal projects suggest a need for more exposure to team-based, production-level development environments.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and problem-solving mindset, essential for an AI Engineer role. The ability to work on diverse projects (civic issues, cheating detection, research automation) suggests adaptability and a willingness to tackle varied challenges. The internship experience, though limited, shows exposure to structured data science workflows and collaboration.