Orchestrated an end-to-end workflow using AWS Lambda, MailSlurp webhooks, Amazon Textract, and OpenAI’s GPT function to automate the parsing and extraction of invoice details from various freight-related email attachments, enhancing operational efficiency.

Created a npm package that automates end-to-end AWS infrastructure provisioning for queuers using Pulumi.

Led the creation of a robust social media platform with Next.js, Prisma, Clerk, and Vercel, as a compelling proof of concept for building an in-house frontend application dedicated to container lifecycle management.

Built a tool to track changes to Logging/Experimentation headers along a request lifecycle within services, decreasing the MTTR (Mean Time to Repair) by 80% and the MTBF (Mean Time Between Failure) by 50%.

Migrated the Logging and Experimentation schema CRUD UI tool from Jinja to React along with service separation for its APIs, decreasing deployment time by 58%.

Owner of multiple full•stack components within an internal Logging and Experimentation platform.

Member of the on•point rotation team.

Prepared Technical Specifications for tasks/features.

Owner of multiple full-stack components within the product.

Participated in the on-call rotation team for sales urgent (high-priority bugs)

Drafted technical specifications for multiple tasks/features.

Spearheaded the addition of Machine Learning Applications to the product to enhance its capabilities.

Designed the architecture for the Machine Learning system.

Led the Machine Learning Team to orchestrate a system to predict the Time to Close an email helping customers make a calculated decision during email assignments.