Feature leading and developing features for Atlassian's Cloud Security team.

• Joined as one of the first engineers at Aquabyte, a multinational company that develops sustainable aquaculture solutions using Machine Learning, underwater hardware, and cloud based technologies.

• Designed and implemented the initial MVP Customer Dashboard that surfaces sea lice level data in the form of real time overview pages and line/bar graphs using React, Redux, ChartJS, and Node.js, helping the company raise over $10 million in Series A funding.

• Architected and implemented a Bounding Box Labeling Interface System using React, Redux, HTML Canvas, OpenCV.js, and Node.js used by a team of annotators to produce training data for internal Machine Learning algorithms.

• Created an Internal Dashboard to manage users, view live camera feeds, and manage deployed fish pens using AWS SQS/SNS, Lambdas, DynamoDB, Node.js, Express.js, React/Redux, and Mocha/Chai for unit tests.

• Worked with various tools from the AWS suite, such as Elastic Beanstalk, RDS, Route53, CloudFront, API Gateway, and S3, to manage deployments and build features.

• Migrated the codebase from a third party user management system to an in-house, JWT based one made using bcrypt, and passport.js.

• Provided mentorship to a junior engineer on dashboard features and high impact projects, including a customer facing API.

• Led Frontend development for Memebox, a $160 million venture-backed Y-Combinator company, on their global e-commerce, recommendation, and community platform for Korean cosmetics.

• Reduced page load time by 34% for web (3.3s to 2.1s) and 55% for mobile web (5.3s to 2.4s) by segmenting application into feature-based modules to utilize Angular Lazy Loading. Prioritized e-commerce code to reduce application size by 53% (5.31MB to 2.54MB).

• Implemented brand landing pages, affiliate cookie tracking, ambassador shop pages, ambassador revenue dashboards, product description pages, checkout/cart flow, and community features (hashtags, user onboarding, personalized UGC feed, custom product tag-ging) from PRDs and InVision mockups using HTML, Sass CSS, Typescript, jQuery, Angular 4, NodeJS, and SemanticUI.

• Implemented foundational features in the front and back-end for a real-time, collaborative, enterprise document automation web application based on TypeScript, Node.js, Koa, engine.io, and React.

• Interfaced with the Salesforce API using JSForce.js to insert Salesforce Opportunity data into dynamically generated word documents.

• Implemented underlying front-end UI framework components such as tooltips, dropdowns, checkboxes, buttons, dialogs, and input fields used in over 90% of the application using React and PostCSS.

• Implemented and optimized features for the real-time, OOXML-based online word processor such as Table of Contents, rendering, document sharing permissions, editor UI/UX, comment assignments, and internal/external user comment filtering.