Architected and scaled a high-throughput distributed system processing billions of messages daily, directly enabling the company’s strategic expansion into the enterprise market.

Led a cross-functional team of 4 developers through the full SDLC, from technical design and capacity planning to the implementation of mission-critical scaling and cost-optimization features.

Doubled peak throughput from 500M to 1B+ messages per hour while reducing message coordination latency by 90% through architectural refactoring.

Accelerated team velocity by spearheading the adoption of AI-driven development tooling and establishing a technical mentorship program for junior engineers.

Drove engineering excellence by conducting technical interviews and defining high-bar hiring standards during a period of rapid team growth.

Rapidly developed a high throughput patient communication platform that allows medical administrators to communicate with patients through SMS and email with Azure, MongoDB, and Node.js

Built service with Node.js that replaced plain text proprietary content with OAuth links that allow business to sell content as subscriptions instead of one time sales

• Carried features from planning through full stack implementation in a Java, Spring, and MySQL backend with JavaScript and SCSS frontend

Dockerized a series of Ruby microservices in order to bring applications in line with AQUA security scans, which was a crucial step in cloud based Kubernetes deployment

Created automated build pipelines with Jenkins/Groovy to schedule sequences of Java based automation tasks and alerts to reduce the need for manual processes

Built and maintained RESTful API with Java/JAX-RS to expose database information in order to make access to data more seamless for QA and business analysts

• Developed C library to replace time consuming Python functions, which increased the speed of such functions by factors of over 100x (NumPy/Ctypes/CProfile)

• Used profiling tools to benchmark performance and identify bottlenecks