About Me

Overview

I am a software engineer. I started programming when I was 14 as part of a class in my freshman year of high school. My first programming experience was using GameMaker, before moving on to Visual Basic, C++, and Java. In college, I worked primarily with Java, Python, and JavaScript.

I initially attended George Fox University, a small college in Newberg, Oregon. After a couple years and a pandemic, I decided to transfer to Loyola Marymount University in Los Angeles, California. I was primarily interested in their courses for Artificial Intelligence. During my time there, I also helped create a beta experience called Hyprlink. It was an events app to help students find events around the city and RSVP for them.

During the summer of 2021, I got an internship at Intel. I worked in technical documentation automation, writing automation services for the technical documentation team. During that time, we migrated some old webapps to newer frameworks and significantly improved load times (in some cases, it turned 5+ minute waits into mere seconds!). I was responsible for completely automating a manual QA validation process, which I was able to achieve before ending my internship in May of 2022.

In May, I accepted an offer from Amazon to join the Alexa Shopping org. I spent a short time there before transferring to the Audible Creator Marketplace org. I've been here ever since, focusing on improving the customer experience and bringing ACX.com into the 2020s, after it spent so long stuck in the 2000s. One of my main achievements has been leading a project which migrated ~60% of all the user flows to a new framework, all while adding new features, refactoring old logic, and upgrading the UX.

Outside work, I do a lot of reading. You can see what I read in my Read Every Day initiative. Additionally, my friends and I sometimes have fun and do hackathon projects. We've got one in the works which uses generative AI, it's super fun. Can't wait to share it.

Now, let's get to the boring resume stuff.

Skills

Languages

TypeScript

JavaScript

Java

Python

HTML/CSS

SQL

AWS Cloud

SNS

SQS

Lambda

CloudWatch

CDK

Route53

Miscellaneous

React.js

React Query

Axios

Redux

PostgreSQL

Lombok

Slf4j

Spring

Hibernate

Figma

Experience

Amazon: Software Development Engineer I

May 2022 - Present

Lead the migration of primary customer workflows for audiobook creation from JSP to TypeScript using React.js, resulting in a refreshed experience for 70% of all user flows in the application and improving page load time by 30% serving 80k customers per day.
Optimized main development package test suites to reduce total run time of tests by 300%, allowing faster iterations and more frequent delivery to customers.
Stremlined onboarding developer workflow to reduce time to first story by up to 2 weeks

Intel Corporation: Software Engineer Intern

June 2021 - May 2022

Performed a project rewrite, converted legacy Ruby webapp into enhanced React app using a Model-View-Controller pattern to enhance source code organization
Optimized the React app and reduced load times by up to 90% compared to legacy Ruby app through asynchronous API calls, better page design, and lazy loading methods
Improved user satisfaction by iteratively reimagining the webapp UI to be friendlier and optimized for faster workflow, while maintaining core attributes to maintain user muscle memory
Overhauled legacy Ruby semi-automation scripts used to process various files; redesigned the automation process in Python to require minimal human interaction, saved the company hundreds of dollars each week.
Designed and implemented a backend API using Python Flask, nginx, and redis to enable job queuing, and Kubernetes/nginx for load balancing by automatically deploying more pods when traffic became overwhelming.

Loyola Marymount University: Frontend Engineer Intern

September 2020 - May 2021

Implemented several front end features such as a sign-up page using functional, component-based React.js for production
Redesigned the user interface with Figma to create a friendlier UX/UI based on feedback from professionals in web design
Streamlined backend integration testing through use of a Docker image
Maintained an agile workflow through the use of asynchronous task delegation, weekly review meetings, and a task backlog similar to scrum to improve overall efficiency of the development process

Projects

AI Gam

January 2024 - Present

Designing a system for playing a charades-like game which utilizes LLMs to generate content.
More to come!

Basilisco: Social Platform for Gen AI

March 2023 - May 2023

Designed a web application using React.js, Node.js, and Python that allowed users to create an account and share art generated natively in-app using a self-hosted gen-ai model.
Self-hosted a generative AI model to reduce operational costs by up to 80% when compared to using OpenAI APIs.
Utilized AWS SNS, SQS, and Lambda to trigger requests to the server for executing art generation requests.

Hyprlink: Fun Found Fast

August 2021 - August 2022

Designed a Swift application with Node backend that showed popular public events in the users geographic area on a map, and get invited to private events.
Constructed an intelligent algorithm that can determine the trustworthiness of accounts on the application to assure the safety of event attendees and hosts.
Built a complex account network using AWS RDS and connected it to the Swift frontend using Node.js and Express.js to enable full CRUD capabilities.

PacMan Capture The Flag

March 2021 - May 2021

Designed a PacMan machine learning agent that made use of reinforcement learning to play an adversarial game of Capture the Flag against other similar agents
Created a feature extractor that decomposed state-action spaces into useful features that our agent could attend to, learn from, and weight in order to make optimal moves
Composed a reward function that provided a balanced set of rewards for positive and negative outcomes of movements made by the agent to encourage meaningful decisions

Bouncer Bot

July 2020 - June 2021

Published a Discord automation bot built with Python that provided two-factor authentication email sign-in verification features for the official school chat server
Ensured server security with domain-locking functionality, allowing administrators to force users to use their organization emails when joining the organization Discord server
Utilized the Gmail and Discord Bot APIs to handle email distribution and asynchronous messaging between the bot and end users

Z-RACE Info Center

March 2021 - April 2021

Assembled a webapp information hub using React.js, MaterialUI, Node.js, and hosted through Firebase to assure the community could access any information about the development of our game in an easy and simple manner
Reduced repetitive user feedback, bug reports, and suggestions by 50% through use of the webapp to keep users informed
Improved overall community satisfaction by implementing status indicators on all user suggestions and bug reports, assuring our awareness of the issues and ideas

Check it out!

DocuMed

July 2020 - December 2020

Designed a web-based system used to apply learning disability accommodations to university classes in the interest of streamlining the accommodations process for students with learning disabilities
Developed a front end mockup of the website as a proof-of-concept using React.js, Node.js, MaterialUI, and hosted with Firebase
Improved overall design of the site through an iterative design process and direct user testing to increase accessibility and ease of use for all users

Check it out!

Salary Predictor

November 2020 - December 2020

Utilized Python sklearn to perform Logistic Regression on a 47,000-value Pandas DataFrame to predict salaries of individuals based on the real income data
Observed, sanitized, and stored over 47,000 lines of unorganized and incomplete data from the UCI Adult Income dataset using sklearn's OneHotEncoder and Pandas DataFrames
Implemented an email spam filter built with the same Logistic Regression model as the Salary Predictor to increase familiarity of sklearn and Pandas libraries, as well as building logistic regression models