I refactored the .NET backend for a trading platform, implementing standard patterns that resulted in a 10X increase in trading capacity and a significant reduction in error and support issues, from over 12 per week to less than one per day. During the frontend refactoring, I utilized React.js and TypeScript, which enhanced code maintainability, improved client performance, and provided a better user experience.I developed .NET web services to receive and process TBA trade events with zero fault rate and created another .NET web service to handle time-consuming trade accounting procedures asynchronously. By offloading the accounting burden to this web service, I was able to significantly increase the platform's performance, scalability, and supportability.I collaborated with multiple teams, including Data Engineering, Platform Engineering, and Risk & Research, to build REST.NET core APIs and web clients that access Snowflake databases, enabling efficient analysis and reporting. Additionally, I utilized Python to develop an AI trade suggestion engine with machine learning capabilities, further enhancing the platform's trading efficiency.

I resolved issues in outdated trading platforms, ensuring the firm's ability to effectively manage billions of dollars. By employing proactive maintenance and upgrades, I significantly enhanced the performance and reliability of the trading platform, helping to safeguard and optimize critical financial operations.

I modernized and relaunched customer-facing websites using a tech stack that included Angular, Sass, and Node.js.

To ensure the highest quality, I developed comprehensive test scenarios and conducted thorough testing, meticulously documenting each test case. Additionally, I implemented XUnit and Selenium for automated testing, which significantly reduced the manual regression testing workload.