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AI Engineer with less than a year in Artificial Intelligence & Scalable Backend Systems
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Dynamic Computer Science Engineer with a focus on Artificial Intelligence and Scalable Backend Systems. Proven expertise in building production-ready RESTful APIs using FastAPI and deploying containerized applications with Docker. Experienced in training and fine-tuning LLMs and optimizing Computer Vision algorithms for CPU-based environments. Strong background in cloud infrastructure (AWS/DigitalOcean) and a track record of delivering high-performance, end-to-end software solutions.
FAST NUCES
BACHELORS IN COMPUTER SCIENCE · Computer Science
August 1, 2021 – June 30, 2026
Federal Board of Intermediate and Secondary Education
Higher Secondary Education
June 1, 2018 – May 31, 2020
D-TECH & CONSULTANCY
AI BACKEND ENGINEER
January 1, 2025 – August 1, 2025
Islamabad, Islamabad Capital Territory, Pakistan
Multimodal RAG & Semantic Search Engine
January 1, 2025 – August 1, 2025
Architected an end-to-end RAG system capable of parsing complex PDFs (text + charts) using a dual-stream embedding architecture (Sentence-BERT & CLIP). Integrated 4-bit quantized Mistral-7B via Hugging Face, utilizing Chain-of-Thought (CoT) prompting to reduce hallucinations by 25%. Optimized retrieval latency to sub-100ms by indexing high-dimensional vectors in FAISS. Built a Semantic Search engine using a BERT Cross-Encoder, achieving a state-of-the-art NDCG@5 score of 0.96.
Virtual DNA – Genetic Trait & Kinship Analysis
January 1, 2025 – August 1, 2025
Architected a multimodal ML system to predict genetic traits and familial connections using PyTorch, achieving high-accuracy kinship verification. Engineered a Siamese Neural Network with contrastive loss to analyze fingerprint similarity and verify biological relationships. Developed a Computer Vision pipeline using MTCNN for face detection and a fine-tuned MobileNetV2 for automated skin tone classification on the CelebA dataset. Implemented neural regression models on the Galton dataset to forecast physical traits and developed rule-based logic for offspring blood group prediction.
AI Career Copilot – Full-Stack Agentic Application
January 1, 2025 – August 1, 2025
Architected a full-stack platform using FastAPI and Next.js 15, utilizing Llama 3.1 to transform unstructured PDF resumes into relational JSON data with strict Pydantic schema enforcement. Engineered a semantic job-matching engine using FAISS and BGE Embeddings, moving beyond keyword search to achieve context-aware similarity ranking with sub-100ms latency. Implemented a Multi-Agent feedback loop that simulates technical interviews, providing quantitative scoring and qualitative critique on user responses through a custom-built interactive UI. Developed a real-time AI roadmap generator using Server-Sent Events (SSE) and Asynchronous Python to stream markdown-formatted study plans chunk-by-chunk for an optimized user experience.
Real-Time Traffic Analysis System (Computer Vision)
January 1, 2025 – August 1, 2025
Developed a high-performance vehicle tracking system achieving 60+ FPS on standard CPU hardware, eliminating the need for expensive GPU resources. Implemented Background Subtraction (MOG2) and Centroid Tracking algorithms to quantify traffic flow with 95% accuracy. Designed a preprocessing pipeline using Morphological transformations that reduced environmental noise/shadow interference by 15%.
Cultural Fit Analysis
The candidate's portfolio showcases a broad range of AI/ML applications, from multimodal RAG to computer vision and agentic systems, indicating a strong curiosity and willingness to tackle diverse technical challenges. The focus on building production-ready, scalable systems aligns well with a results-oriented culture. The mention of optimizing for CPU and reducing hallucinations suggests a practical, efficiency-minded approach. The candidate's education is ongoing, which might indicate a continuous learning mindset.
Soft Skills & Operational Fit
The candidate's project descriptions indicate strong problem-solving abilities, a focus on performance optimization, and an understanding of full-stack development. The ability to work on diverse projects (RAG, CV, full-stack AI agents) suggests adaptability and a proactive approach to learning and applying new technologies. The professional summary highlights a track record of delivering high-performance, end-to-end solutions, which is crucial for operational fit in a senior role.