Oct 2018 - Sept 2020
WIDA, UAE Full- Stack Developer
Effectively planned and documented comprehensive project requirements for client projects, including a dating app (Flutter), e-commerce websites (WordPress, Django, Flask, Next.js, Shopify, Web flow, Magento etc.), rental warehouse space cost calculator (React, WordPress), and video streaming platform using Nodejs (JavaScript, Typescript, Express.js, Sequelize), ensuring clear communication and timely delivery.
Feb 2022 - Feb 2025
UAS, UAE Senior Full Stack Engineer
Spearheaded feature enhancements and backend architecture upgrades for a high-impact product (Trip Management Software), personally implementing core components using JavaScript, Typescript (Node.js), NestJS, ExpressJS, TypeORM, MySQL (main), Redis (for caching and real-time updates), and MongoDB (for logging and chat component). Engineered scalable and secure RESTful APIs and real-time communication via WebSockets (Socket.IO), contributing to a 25% overall increase in user satisfaction over six months by proactively transforming user feedback into impactful product improvements.
Sept 2020 - Feb 2022
Beunique Group Lead Software Engineer
Developed and deployed computer vision pipelines using Nodejs (JavaScript, Typescript, Express.js) and TensorFlow for automated NSFW image detection, achieving 84%+ accuracy on user-uploaded content. This reduced manual moderation by 80%, enhanced user experience, and ensured compliance with platform policies, significantly boosting user trust and engagement on the app.
Oct 2016 - Oct 2018
Freelance Full Stack Engineer
Worked with 7 organizations from around the world, developing systems that include e-commerce, booking, portfolio, blog, and multilingual functionalities (using WordPress, Django, Flask, Ruby on Rails, Shopify, Web flow, Magento etc.).
Feb 2022 - Feb 2025
UAS Senior Full Stack Engineer
Developed an AI-powered agent to automate email responses and provide real-time chat support via WebSockets, leveraging Python, TensorFlow, and OpenAI’s GPT models. Designed NLP pipelines using LangChain with a Retrieval-Augmented Generation (RAG) approach, integrating a vector database for real-time knowledge retrieval. Fine-tuned GPT models on domain-specific data to enhance contextual accuracy, achieving 70%+ response accuracy while optimizing inference costs.