Everton – .NET, Typescript, React

This project automated processes related to condominium management, such as: billing tenants / unit owners and generating monthly reports. The initial version of this product was already in use, and new features are continuously being added to facilitate actions such as allowing tenants to make reservations of common spaces.

Everton was in charge of the following:

• created front-end and back-end architecture using the latest .NET 9;
• designed the database using the Entity Framework code-first approach;
• implemented Cloud integrations (GCS - secret management, AWS - S3 and SES);
• integrated solution to 3rd party banking services APIs.

This project was an AI-powered Transportation Management System (TMS), where Everton was tasked with tackling performance issues, implementing new features, and collaborating on migrating legacy ASP.NET code to React.

Everton's contributions included the following:

• identified and resolved critical performance issues caused by inefficient entity framework usage, reducing load times by up to 80%;
• led the implementation of an impersonation feature using oidc-login and secure jwt storage;
• enabled deprecation of a legacy master password system, eliminating a major security liability.

This project was a social media automation and analytics platform designed to help businesses, marketers, and content creators manage their online presence more effectively. It streamlined the process of scheduling posts, tracking engagement, and analyzing performance across multiple social media channels. Instead of manually switching between platforms, users have a centralized dashboard to handle everything.

The main scope of Everton's responsibilities were:

• implemented a new interface to allow users to generate content using AI;
• developed time-critical back-end integration to meet the deadline for SOCi's biggest contract at the time;
• refactored front-end code on frequently used page to reduce load time by 50%;
• solved long-standing bug related to RSS feed parsing, which prevented client churn.

The client was the largest investment bank in LATAM & the product was the automation of processes related to receiving and processing incoming client investment transactions.

Among others, duties included the following:

• developed robust and scalable microservice APIs;
• used queue-based solutions to handle the dynamic request load;
• implemented backend solution using Redis to solve concurrency issues and improve performance;
• solved long-standing concurrency issue by applying MySQL best practices.