Developed a sophisticated Retrieval-Augmented Generation Pipeline for a Large Language Chatbot, enabling seamless database queries and delivering personalized, comprehensive assistance to users.

Lead a group of five developers in the completion of a full-stack web application using DyanmoDB, GraphQL, AWS Cognito, JavaScript, and React.

Developed a Specialist Portal that matches patients with nearby healthcare specialists using company APIs and AWS.

Currently working on migration of company technology to AWS (S3, AmazonSQS, Amplify, JobRunr).

Worked on end-to-end AI automated response feature through the implementation of a Large Language Chatbot model.

Enhanced a Large Language Chatbot to streamline meeting scheduling for businesses and clients, seamlessly integrated with Google Calendar.

Implemented OAuth2.0 integrations with various platforms such as Google, Calendly, and Hubspot.

Created robust APIs for frontend team to connect with server.

Led the design and assisted with the development of a dynamic "Resend Invitation" page by leveraging React.js, Node.js, HTML5, and CSS.

Created a responsive user interface using HTML5 and CSS, while implementing backend services and REST APIs to ensure smooth functionality.

This application optimized over 80% of work done by Movius’ USB support team.

Worked on the development of a Sentiment Analysis Model in Python using NLP, Recurrent Neural Networks (RNN), Pandas, and Numpy in order to predict the emotions of a given passage.

Contributed to the production stage of a high-profile project that was successfully deployed across renowned financial institutions, including Bank of America, JP Morgan, and Wells Fargo.

Utilized transformer models to retrieve sentiment from text and audio.