Minahil Azaz

AI Engineer with a CS degree from UET Lahore and hands-on experience building agentic systems, RAG pipelines, and full-stack AI applications in production. Proficient with LangChain, LangGraph, FastAPI, vector databases, and cloud deployment. Experienced with multi-modal AI, NLP/ML frameworks (PyTorch, TensorFlow, Hugging Face), and REST/microservice APIs.

First author of a Springer Nature publication on AI-driven security systems; actively building with agentic protocols (LangGraph, MCP-compatible flows) and conversational AI systems.

Full Stack Engineer at REMOTEDEV LIMITED (2026-01 – Present)

• Developed full-stack web applications using React.js, React Native, Node.js, and Express.js for production deployments.
• Built and integrated RESTful APIs for authentication, user management, and third-party service connectivity — relevant to microservices and API-first AI agent architectures.
• Worked with MongoDB and SQL databases for scalable data storage; applied data-pipeline thinking for structured/unstructured data across platforms.
• Contributed to feature development, debugging, and testing in an agile team environment.

AI/ML Intern at Dot Republic Media (2025-09 – 2025-12)

• Designed a multi-modal AI pipeline (NLP + Computer Vision) using Sentence Transformers, OpenCV, and RapidFuzz reducing manual content-tagging effort by ~60%.
• Built AI-driven automation pipelines with Google Apps Script; eliminated ~5 hrs/week of manual reporting and demonstrated task-orchestration thinking.
• Developed a Flask analytics dashboard for real-time ML model performance monitoring, used directly by stakeholders.
• Optimised training datasets and model pipelines, reducing iteration time by ~30% and improving classification accuracy.

BS in Computer Science – University of Engineering and Technology (UET) (2021-12 – 2025-05)