• Contributed to an AI-driven loan approval platform integrating Anthropic Claude 3 for predictive scoring, default estimation, and risk assessment, collaborating with AI and credit risk teams, gathering requirements, and documenting specifications in Confluence and Figma.

• Implemented Spring Boot microservices using gRPC and Kafka for real-time credit scoring.

• Improved system reliability by 19% through resilient event processing and policy evaluation.

• Designed RESTful APIs including /loan-approval-forecast, /customer-risk-profile, /fraud-alerts, and /customer-insights, collaborating with analytics and compliance teams to deliver real-time predictive insights, fraud detection, and hybrid database integration, reducing API latency by 22%.

• Built dashboards and visualizations with React, TypeScript, Redux, and hybrid PostgreSQL/AWS Aurora databases, integrating Kafka streams for live KPI updates, enabling analysts to monitor credit risk, AI predictions, fraud alerts, and agentic AI recommendations, improving reporting speed by 17%.

• Executed security implementation using Spring Security with OAuth 2.0 and JWT authentication, ensuring SOC 2, PCI DSS, and FFIEC compliance, performing unit and integration testing with JUnit, Mockito, and Postman, coordinating with security and compliance teams.

• Managed CI/CD pipelines with GitHub Actions, Docker, and Kubernetes (AWS EKS), collaborating with DevOps teams for deployment, observability, uptime, and monitoring, documenting workflows and best practices in Confluence and internal runbooks, improving deployment efficiency by 18%.

• Architected the Real-Time Ride Analytics project, developing Spring Boot microservices for Uber-scale event processing, collaborating with product and design teams, gathering requirements, ensuring low-latency, reliable ride and engagement tracking across India.

• Engineered asynchronous services for Trip Event Processing, integrating Redis, Azure Cache, and connection pooling, optimizing microservice communication, reducing API latency by 15%, enabling high-throughput, event-driven processing for millions of concurrent ride requests.

• Designed fault-tolerant microservices with circuit breakers, service discovery, and load balancing in the Driver-User Engagement project, integrating backend WebSocket support, ensuring 50K+ concurrent event handling, improving platform scalability and resilience by 12%.

• Implemented secure database solutions for User and Trip Management, optimizing PostgreSQL schemas, indexing, query tuning, enforcing encryption-at-rest and in-transit, using dynamic RBAC and JWT, reducing authentication incidents by 10%, ensuring data security and compliance.

• Developed React dashboards for the Operational Insights project, integrating REST APIs and WebSockets, delivering real-time visualization of ride activity, campaigns, and retention, enabling informed operational decisions, improving decision-making efficiency by 17%.

• Integrated observability and monitoring using Azure Monitor and Grafana for Ride Platform Services, tracking system health, event throughput, and failures, enabling proactive issue detection, reducing downtime, and improving reliability for millions of users globally.

• Collaborated with DevOps and product teams on Global Ride Service Deployments, implementing Helm charts, blue-green strategies, and deployment runbooks, optimizing backend performance, caching, asynchronous processing, and ensuring seamless, low-latency experiences for millions of users.