I’m a generalist Software Engineer with a strong foundation in backend development, systems engineering, and workflow automation. My experience spans building backend-heavy applications, working with Python, Docker, and AWS, and delivering clean, reliable solutions that simplify complex technical problems.
I also bring graduate-level exposure to AI through my master’s and side projects, giving me a solid understanding of modern tooling without overstating specialization. Overall, I thrive in roles where ownership, clarity, and end-to-end problem solving matter most.
Built an end-to-end ML workflow for predicting heart failure mortality, including data preprocessing, model training, experiment tracking, and containerized deployment on AWS for scalable inference.
Designed and implemented automated infrastructure deployment pipelines, reducing deployment time by 70% and eliminating manual configuration errors.
Developed a distributed e-commerce platform with independent microservices for inventory, payments, and orders. Handles 50K+ concurrent users.
Federal Reserve Bank of Richmond
Designed and maintained cloud infrastructure, automated data workflows, and implemented testing and reporting solutions to improve system reliability and operational efficiency.
Federal Reserve Bank of Richmond
Automated infrastructure image creation and integrated security tools to streamline delivery and ensure compliance.
Georgia Institue of Technology
Virginia Commonwealth University
I’m happy to connect about projects, ideas, or opportunities to contribute to your team’s work.