• Orchestrated microservices for Citi’s risk-scoring and transaction-validation pipelines using Spring Boot, Spring MVC, and Spring Security (JWT), reducing API latency by 28% and strengthening fraud-detection request handling across high-volume trading channels.

• Integrated event-driven integrations with upstream pricing and customer-profile systems using Kafka, enabling near-real-time data propagation and cutting reconciliation delays by 35% for regulatory and risk-reporting teams.

• Developed front-end modules in React.js and Redux, building secure dashboard workflows for AML/KYC case investigators and increasing case-resolution efficiency by 22% through optimized API orchestration and UI state management.

• Delivered containerized risk-evaluation workloads to AWS EKS with CloudFormation templates and EC2 autoscaling rules, improving compute cost efficiency by 18% while ensuring compliance with Citi’s internal cloud-security standards.

• Enhanced platform observability by configuring centralized monitoring using the ELK Stack, authoring structured logging patterns and correlation IDs, which reduced incident triage time by 33% across distributed microservices.

• Accelerated delivery through GitHub Actions CI/CD, GitHub Copilot, and Chat GPT API–driven AI-assisted code generation, cutting code review effort by 25% and improving test coverage via automated JUnit pipelines and static analysis.

• Spearheaded scalable backend services using Java, Spring Boot, and Spring Data JPA for customer-account and policy-management systems, cutting API response times by 27% and improving SLA adherence across high-traffic production workloads.

• Crafted interactive React.js UI components and operational dashboards integrated with REST APIs, reducing manual processing effort for support and billing teams by 30%.

• Architected and implemented event-driven architectures with RabbitMQ, enhancing asynchronous workflows for notifications, batch processing, and insurance quote lifecycles, resulting in a 35% improvement in throughput during peak usage.

• Deployed and optimized cloud-native components on AWS (API Gateway, RDS, DynamoDB, SES) to establish secure, automated data flows, decreasing infrastructure overhead by 20% and enabling fully automated customer communication pipelines.

• Strengthened system reliability by configuring Grafana and AWS CloudWatch dashboards, custom alerts, and traces, reducing incident detection time by 40% while improving test stability through Mockito unit tests integrated within GitLab CI/CD.

• Established enterprise-grade UI modules using Angular, TypeScript, and Tailwind CSS, integrating them with REST and GraphQL services to reduce page load time by 22% and improve task completion efficiency for internal operations teams.

• Built backend components with Java, Spring MVC, and Spring Batch to automate data ingestion and nightly reconciliation workflows, lowering manual processing effort by 40% and increasing batch reliability across systems.

• Enhanced data performance by optimizing relational models, indexing strategies, and stored procedures in PostgreSQL, achieving a 30% decrease in query execution time for reporting and billing APIs under production load.

• Containerized microservices using Docker and enabled consistent multi-environment deployments via Jenkins CI/CD, reducing release cycle time by 25% and improving deployment stability.

• Improved development quality using Test-Driven Development (TDD), executing comprehensive unit and integration tests with Postman and CI pipelines, and maintaining detailed design documentation in Confluence, boosting defect detection by 35% before UAT.