I build production AI systems and the full-stack products around them. Over seven years I've shipped RAG pipelines, multi-agent workflows, voice agents, OCR and computer vision systems, along with the React, Next.js, Angular, Node.js, Django, and FastAPI applications that put them in front of real users.
Most recently at Turing, I worked as a Senior LLM Engineer on Terminal-Bench and trained computer-use agents for Meta. That meant writing the tasks, evaluations, and validation pipelines that frontier models are tested against. Before that I was a Tech Lead at Devsinc running a team of seven engineers, and an ML Engineer at PackageX building OCR and document processing for logistics.
My work spans logistics, fintech, healthcare, HR, education, e-commerce, and construction estimation. Recent products include an AI grading platform, a compliance automation tool, and a contractor estimation system, each built from architecture through deployment.
I care about software that holds up in production: clear architecture, tested code, structured LLM outputs, and automation that saves people real time. I hold an MS in AI from NUST and a BS in Computer Science from FAST-NUCES.
Worked on AI training, evaluation, and agentic workflow projects for advanced LLM systems.
Contributed to SFT, RLHF, prompt evaluation, benchmark design, data validation, and QA workflows across coding, reasoning, multimodal, and desktop-agent tasks. Improved task reliability through structured feedback and evaluation pipelines focused on accuracy, tool use, instruction following, and real-world task completion.
Built production AI-enabled web applications using React, Angular, Node.js, Python, Django, Flask, and REST-based backend services.
Delivered AI feature integrations, data preprocessing workflows, backend automation, dashboards, API design, and scalable client-facing modules. Later led a six-member engineering team, performing code reviews, coordinating sprint delivery, and maintaining quality across full-stack and AI/ML components.
Developed logistics-focused web and mobile workflows for OCR scanning, package intake, mailroom operations, inventory visibility, real-time tracking, and recipient notifications.
Used React, React Native, Django REST Framework, Node.js, Python, and API integrations to support package scanning, label recognition, operational dashboards, and internal logistics automation. Contributed to performance improvements, backend reliability, and AI-assisted logistics product delivery.
Developed and maintained business websites, admin panels, employee management systems, and internal tools using MERN and MEAN technologies.
Worked with React, Next.js, Node.js, Express.js, MongoDB, Angular, JavaScript, authentication flows, reusable UI components, API integrations, and database-driven workflows. Supported testing, bug fixing, performance optimization, feature enhancements, and long-term maintenance.
MS, Artificial Intelligence
Completed a Master of Science in Artificial Intelligence, strengthening expertise in machine learning, large language models, computer vision, deep learning, and applied AI system development.
BS, Software Engineering
Completed a Bachelor of Science in Software Engineering with a foundation in software architecture, data structures, algorithms, databases, web development, and full-stack application engineering.
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