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AI Engineer with 3+ years in AI Solutions & Large Language Models
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Experienced and results-driven AI Engineer with 3+ years of experience in AI solutions, specializing in designing and deploying scalable AI systems across machine learning, computer vision, and large language models (LLMs). Proven ability to automate complex workflows, build multi-agent systems, and deliver high-impact AI solutions that improve efficiency and accuracy. Experienced in real-time AI systems, RAG pipelines, and intelligent automation, with a strong focus on performance, reliability, and measurable business outcomes.
Air University
Bachelor of Science · Computer Science
N/A – Present
Devnex
AI Engineer
June 1, 2025 – Present
Islamabad, Islamabad Capital Territory, Pakistan
Mwan
AI Engineer
May 1, 2025 – April 1, 2026
Islamabad, Islamabad Capital Territory, Pakistan
Vision X
AI Engineer
December 1, 2024 – April 1, 2025
Islamabad, Islamabad Capital Territory, Pakistan
Eliza OS - Agentic AI + RAG + Plugins
June 24, 2026 – Present
Engineered a production-grade multi-agent AI system on Eliza OS framework, enabling fully autonomous interaction across social platforms including company forums and Twitter. Designed and deployed 5 distinct AI personas per company - including a Devil's Advocate agent that critically challenges discussions using company-specific data, and an Inquisitive Analyst agent that autonomously generates incisive questions by analyzing forum posts, comments, and internal company knowledge - driving deep, context-aware audience engagement. Developed custom Forum and Twitter plugins with persona-driven logic, replacing manual human interaction and handling 1,000+ autonomous interactions per workflow cycle with a 40% increase in engagement efficiency. Implemented RAG-backed persona behavior, grounding each agent's posts, replies, and comments in real company data to ensure brand-consistent, contextually accurate autonomous discourse at scale.
Hatel Retail AI for Product Detection & Classification - CV + NLP
June 24, 2026 – Present
Designed an end-to-end computer vision and NLP inference pipeline integrating a custom-trained YOLOv11x model fine-tuned on a proprietary product dataset, achieving 94% detection accuracy with precise bounding box localization and multi-class product classification across 1,000+ SKUs. Optimized model performance through rigorous experimentation with anchor box tuning, IoU thresholds, NMS calibration, and data augmentation strategies (mosaic, random flipping, HSV shifts) to maximize mAP scores across varying image resolutions and lighting conditions. Integrated PaddleOCR for region-of-interest text extraction on detected product zones, achieving 92% OCR accuracy by applying preprocessing techniques including adaptive thresholding and contour-based crop alignment. Downstream extracted text was passed through a fine-tuned SpaCy NER model with custom entity schemas to classify product attributes — including brand, quantity, expiry, and category — into structured, queryable data at scale.
Utter chatbot
June 24, 2026 – Present
Architected a production-grade, multi-tenant RAG chatbot platform serving 100+ enterprise clients with strict tenant-level data isolation across 500,000+ indexed document chunks. Built an asynchronous document ingestion pipeline using RabbitMQ, reducing upload-to-searchable latency by 70% through decoupled background embedding processing. Implemented semantic search with vector database namespace isolation, achieving sub-second query response times with zero cross-tenant data leakage. Designed for horizontal scalability with independently scalable RabbitMQ consumers, supporting 10,000+ daily queries across concurrent enterprise workloads.
AI Engineer Associate
Microsoft Azure
June 1, 2026 – Present
Advance Machine Learning
NAVTACC
June 1, 2026 – Present
What is Data Science
Coursera
June 1, 2026 – Present
Introduction to Python
Coursera
June 1, 2026 – Present
Introduction to Data Modelling PowerBI
sqlbi
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's experience across diverse AI projects (multi-agent systems, RAG chatbots, computer vision for retail and libraries) and leadership roles suggests adaptability and a proactive approach to problem-solving. Their focus on delivering measurable outcomes and improving efficiency aligns well with a results-oriented culture. The breadth of skills and technologies indicates a continuous learning mindset.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through optimizing model performance and architecting scalable systems. Leadership and team collaboration are evident from leading an AI sub-team and contributing across the full product development lifecycle. The ability to translate ambiguous business requirements into robust AI systems indicates strong operational fit and client-facing capabilities.