Contributed to the development of LLM-powered applications by engineering scalable, robust RESTful API endpoints using Flask and Node.js, and optimizing data storage and retrieval processes from MongoDB.

Implemented frontend features to improve visual hierarchy and usability using Javascript, React, and TailwindCSS.

Updated experience generation flow for user interactions through prompt engineering.

Assisted students in understanding content for the following courses: Data Structures and Algorithms, Intro to Programming & Problem Solving, Calculus I.

Developed a LLM-based agentic system for database manipulation through SQL, and deployed and managed language model driven systems in a client environment using real-world data.

Created a chat agent using Langchain that implemented a RAG pipeline to provide product information and assist with customer transactions given an extensive product catalog.

Implemented updates for iterative rollouts on a sales personnel assistant platform designed to boost sales and enhance customer engagement

Implemented app features using React and Javascript that enhanced user experience.

Performed rigorous testing during app development to identify and report software defects

Developed a machine learning model that optimized an ultra-low carbon concrete mixture composed of less than 2% portland cement, drastically reducing its carbon footprint.

Placed first at nationals of the 2022 ASCE Concrete Canoe Competition in the category of final product, and placed fifth overall