Built Java/Spring Boot payment microservices handling 1M+ daily transactions, achieving 99.9% uptime across all production environments.
Deployed 5+ services on AWS EKS and Azure AKS using Docker, enabling auto-scaling that absorbed 3x traffic spikes with zero downtime.
Built CI/CD pipelines using GitHub Actions and Jenkins, cutting release cycles from weekly to daily and reducing manual deployment steps by 40%
Implemented rule-based fraud detection logic using Java pattern matching, reducing false-positive payment alerts by 20%.
Optimized MongoDB query performance using indexing and aggregation pipelines, cutting average API latency by 35%.
Built Splunk monitoring dashboards with custom alert thresholds, reducing mean time to detect production incidents by 30%.
Partnered with product and QA teams across 8 sprint cycles using Agile, delivering all features on schedule with under 2% post-release defect rate.