Developed distributed member workflow platform consolidating eligibility and claims data across 5+ systems usingNode.js, TypeScript, AWS ECS, improving support resolution speed by 30%.

Implemented multi-state eligibility rules engine processing 2M+ monthly requests using Redis caching and rules abstraction, reducing incorrect determinations by 35%.

Migrated legacy monolith into containerized microservices using AWS ECS, API Gateway, and Auto Scaling,

enabling 3x peak Medicare enrollment traffic handling.

Engineered React dashboards used by 300+ coordinators, reducing cross-system navigation time by 25% through API aggregation and client-side caching.

Built real-time supply chain visibility APIs integrating warehouse and shipment systems using event-driven Node.js and AWS SQS, improving inventory accuracy by 30%.

Implemented async order lifecycle services handling 100K+ daily transactions, reducing order delays by 28% using Lambda + SQS decoupled processing.

Optimized time-series order analytics queries in PostgreSQL, improving response latency by 45% through indexing and partitioning redesign.

Delivered logistics dashboards used by 200+ operations users, cutting manual reconciliation effort by 35% via streaming update architecture.

Led development of a digital loan origination and customer risk decision platform supporting 500K+ monthly loan applications, improving approval processing time by 32% using Node.js & React customer workflow interfaces.

Built React customer onboarding and loan tracking interfaces used across multiple retail banking products, improving customer application completion rate by 22% through guided workflow UX improvements.

Implemented loan eligibility decision services processing real-time credit bureau and internal risk signals, reducing manual underwriting dependency by 28% using Node.js rule evaluation engines.

Improved transaction and loan history retrieval performance by 38% by optimizing SQL query design and indexing strategy across high-volume financial transaction tables.

Constructed an enterprise credit risk analytics platform generating rating insights across 10K+ financial entities, improving model evaluation turnaround time by 40% using Java Spring Boot microservices & Angular dashboards.

Built Angular risk visualization interfaces used by 150+ financial analysts, reducing manual risk report preparation effort by 30% through dynamic portfolio and rating model dashboards.

Developed credit risk computation services processing 1M+ financial data records per batch cycle, improving model scoring consistency by 25% using Java multithreaded processing and batch optimization.

Established financial data ingestion pipelines integrating 8+ external market and financial data providers, reducing data latency by 35% using Java ETL services + message queue processing.