Software Engineer at IBM

Designed and developed scalable microservices using Java, Spring Boot, and React, supporting 2M+ active users across internal and client-facing enterprise platforms. Architected and optimized RESTful APIs with OAuth 2.0 and JWT for RBAC. Improved PostgreSQL query performance by 30% through indexing strategies and transaction handling. Built reusable UI components using React and TypeScript, improving dashboard rendering efficiency and reducing page load times by 24%. Strengthened CI/CD pipelines with Jenkins, GitHub Actions, and Docker; containerizing services with Kubernetes-based deployments on AWS, reducing manual deployment effort by 35% and release rollback incidents by 27%. Monitored application health using AWS CloudWatch and centralized logging tools, reducing MTTR by 29% across distributed production systems.

Research Assistant — AI/ML for Retinal Image Analysis at University of North Carolina at Charlotte

Designed CNN and Vision Transformer models for retinal image classification; containerized and deployed inference pipelines via Docker and Kubernetes on AWS EC2, cutting model serving latency by 30%. Developed REST APIs with FastAPI to expose retinal classification endpoints, scalable model access across distributed research workflows. Built automated image preprocessing pipelines with Python and OpenCV, standardizing contrast normalization and augmentation across multi-source datasets. Integrated Grad-CAM heatmaps and mixed-precision GPU training, reducing total model training time by 25% while improving spatial interpretability.