I’m a software engineer currently pursuing my MS in Data Science at the University of Kentucky, with a background in full-stack development and applied AI/ML work. Over the past few years, I’ve built and improved real-world software systems using React, Node.js, Python, PostgreSQL, MongoDB, and REST APIs, with a strong focus on building products that are practical, reliable, and easy to use. In my previous role at Exaltare Technologies, I worked on a full-stack Railway Workshop Management System where I helped turn complex operational workflows into software used for inspections, dashboards, and day-to-day process management. I also contributed to a multi-tenant Beauty Service Management System with secure authentication and scheduling features. More recently, through my AI/ML internship at the University of Kentucky, I built Python-based analysis and evaluation tools for AI-generated transcriptions, improving agreement detection and reducing proofreading effort. I’ve also worked on projects involving RAG, embeddings, retrieval systems, and recommendation systems. What makes me stand out is that I’m comfortable bridging product thinking, software engineering, and applied AI. I like understanding how people actually use systems, then building solutions that are technically solid and genuinely useful. I’m someone who learns quickly, cares about quality, and enjoys solving problems across the stack rather than staying limited to one layer.…I’m a software engineer currently pursuing my MS in Data Science at the University of Kentucky, with a background in full-stack development and applied AI/ML work. Over the past few years, I’ve built and improved real-world software systems using React, Node.js, Python, PostgreSQL, MongoDB, and REST APIs, with a strong focus on building products that are practical, reliable, and easy to use. In my previous role at Exaltare Technologies, I worked on a full-stack Railway Workshop Management System where I helped turn complex operational workflows into software used for inspections, dashboards, and day-to-day process management. I also contributed to a multi-tenant Beauty Service Management System with secure authentication and scheduling features. More recently, through my AI/ML internship at the University of Kentucky, I built Python-based analysis and evaluation tools for AI-generated transcriptions, improving agreement detection and reducing proofreading effort. I’ve also worked on projects involving RAG, embeddings, retrieval systems, and recommendation systems. What makes me stand out is that I’m comfortable bridging product thinking, software engineering, and applied AI. I like understanding how people actually use systems, then building solutions that are technically solid and genuinely useful. I’m someone who learns quickly, cares about quality, and enjoys solving problems across the stack rather than staying limited to one layer.WWWW…