AI Engineer with less than a year in Generative AI & LLMs
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AI Engineer specializing in Generative AI, LLMs, RAG systems, and AI Agents. Experienced in building AI applications, agentic workflows, and intelligent automation solutions using Python, PyTorch, and modern AI frameworks. Strong background in machine learning and real-world AI solutions.
University Of Engineering and Technology Peshawar
Bachelor's · Computer Science
August 1, 2020 – June 30, 2024
K2X Tech
AI/ML (Internship)
October 1, 2025 – May 1, 2026
Peshawar, Khyber Pakhtunkhwa, Pakistan
Drupify
Data Analyst Intern (Internship)
September 1, 2023 – February 1, 2024
Peshawar, Khyber Pakhtunkhwa, Pakistan
Reiju-Ai-Agent - AI-powered legal assistant system
April 1, 2026 – June 1, 2026
Developed an AI-powered system for intelligent document understanding and multi-step reasoning using LLMs and retrieval-based workflows. Designed and implemented a modular agent-based architecture for processing complex user queries with structured decision flows and tool integration.
AI-Powered Healthcare Appointment System - Healthcare
January 1, 2026 – February 1, 2026
Developed an AI-driven healthcare appointment system with text and voice interfaces for seamless user interaction. Implemented conversational AI using LangChain and LangGraph for context-aware booking and automated workflows. Integrated speech-to-text (Whisper) and text-to-speech for voice-enabled scheduling. Built RESTful APIs with FastAPI and managed patient, doctor, and appointment data using MySQL. Automated email notifications for appointment confirmations and updates.
View ProjectFinSolve Role Specific Chatbot System - Fin Tec
June 1, 2025 – June 1, 2025
Developed the FinSolve Role Based Chatbot System, an internal assistant that delivers department specific responses based on user roles. Enabled secure access to organizational information, ensuring each department interacts only with its relevant data.
View ProjectEcommerce Chatbot System - Ecommerce
June 1, 2025 – June 1, 2025
Created an intelligent eCommerce chatbot to handle customer queries, provide personalized product recommendations, and assist with order-related support. Integrated natural language understanding to enhance user experience and streamline the online shopping process.
View ProjectCar Damage Detection - Automotive
April 1, 2025 – April 1, 2025
Built a deep learning model using PyTorch and ResNet to classify car damage into six categories, achieving over 75% accuracy. Developed as a proof of concept for VROOM Cars to enable automated damage assessment.
View ProjectHealthcare Premium Prediction - Healthcare
February 1, 2025 – March 1, 2025
Built a high-accuracy machine learning model to predict health insurance premiums based on user features such as age, BMI, smoking status, and medical history. Conducted data cleaning, exploratory data analysis (EDA), and model selection to meet strict performance benchmarks (>97% accuracy, 10% error deviation for 95% predictions).
View ProjectSymptoScan: AI-Driven Nose-Related Health Diagnosis
September 1, 2024 – September 1, 2024
Built a RAG-based system to diagnose nose-related health issues from user input. Created a chatbot offering medicine suggestions, usage instructions, and warnings. Built with FastAPI and deployed via Flutter for remote user access. Integrated OpenAI models for accurate responses and enabled document saving for specialist review.
Deep Learning
Codebasics
April 1, 2025 – Present
Master Machine Learning for Data Science & AI
Codebasics
March 1, 2025 – Present
Cultural Fit Analysis
The candidate's project portfolio is diverse, covering various applications of AI/ML, which aligns well with an innovative and exploratory culture often found in AI engineering roles. The focus on personal projects and certifications indicates a strong drive for continuous learning and self-improvement. The target role of 'AI Engineer' is well-aligned with the candidate's demonstrated skills in LLMs, RAG, agent systems, and API development. However, the experience level is low (0 years stated, though internships are present), which might require a team that is prepared to mentor and integrate a junior-to-mid level engineer. The projects are primarily personal or academic, which might suggest less experience in a corporate, team-oriented development environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving and a focus on developing practical, user-centric AI solutions. The internship experience suggests an ability to collaborate within technical teams and contribute to continuous product improvement. The diversity of projects (healthcare, legal, e-commerce, automotive) demonstrates adaptability and a broad interest in applying AI across different domains. However, the lack of explicit team-based project descriptions or leadership roles makes it difficult to fully assess collaboration and leadership soft skills.