Digital Banking Platform
As a Senior Full Stack Developer at Bank of America, I was a key contributor to the 'Digital Banking Transformation Platform' (DBTP), working within a team of 12 developers.
I was responsible for developing and maintaining critical features of this platform, which serves both retail banking customers and internal bank employees.
I specifically focused on the payment processing and account management modules, where I developed microservices using Spring Boot and implemented secure REST APIs with Spring Security for OAuth2 authentication.
I worked extensively with our Oracle database, writing optimized queries and implementing JPA/Hibernate for efficient data persistence.
One of my major contributions was implementing real-time transaction notifications using Kafka and WebSocket connections, ensuring customers receive instant updates about their account activities.
On the frontend, I developed responsive React components with TypeScript, integrated Redux for state management, and implemented Material-UI components for consistent user experience.
I also played a crucial role in optimizing API response times by implementing Redis caching, which reduced our database load by 40%. I worked closely with our DevOps team to containerize my services using Docker and deploy them on AWS EKS.
I was particularly proud of implementing comprehensive unit tests using JUnit and Mockito for backend services, and Jest with React Testing Library for frontend components, maintaining a test coverage of over 85% for my code.
I also actively participated in code reviews and mentored junior developers in best practices for both frontend and backend development.
Payment Processing System
As a Senior Full Stack Developer at Chase Bank, I was deeply involved in developing and enhancing the Payment Processing System (PPS).
I worked extensively on the transaction processing microservices using Spring Boot, implementing crucial features like real-time payment validation, fraud detection integration, and multi-currency support.
I developed RESTful APIs that interfaced with various payment gateways and banking networks, ensuring PCI DSS compliance throughout.
On the database side, I worked with both PostgreSQL for transactional data and MongoDB for payment metadata storage, implementing database sharding to handle high transaction volumes.
I implemented event-driven architecture using Kafka for asynchronous payment processing, which improved system throughput and reliability.
One of my key contributions was implementing a retry mechanism with dead letter queues for failed transactions, reducing payment failures.
On the frontend, I developed the payment dashboard using Angular, implementing real-time transaction monitoring using WebSocket connections and NgRx for state management.
I also integrated Grafana dashboards for real-time transaction monitoring and implemented distributed tracing using Jaeger to troubleshoot transaction flows across microservices.
I worked on containerizing these services using Docker and deploying them on Kubernetes in AWS, setting up auto-scaling policies based on transaction volume.
I implemented comprehensive integration tests using JUnit and Mockito, and set up automated CI/CD pipelines using Jenkins.
One of my proudest achievements was optimizing the payment processing pipeline to reduce the average transaction processing time while maintaining system reliability and data consistency.
Loan Origination System
During my tenure at Bank of America, I played a pivotal role in modernizing the Loan Origination System (LOS). I architected and implemented microservices using Spring Boot and Java, focusing on crucial components like credit decisioning, document management, and automated underwriting. One of my significant contributions was developing a rule engine using Camunda BPM that automated loan approval decisions, reducing processing time significantly. I implemented GraphQL APIs for the frontend to efficiently fetch complex loan application data, reducing unnecessary data transfer. For data persistence, I designed a hybrid database architecture using Oracle for transactional data and MongoDB for document storage, implementing database partitioning strategies for improved performance. I developed event-driven workflows using Kafka for real-time credit bureau integration and status updates. On the frontend, I led the development of a modern interface using React with TypeScript, implementing form validation logic, document upload features, and real-time status tracking. I integrated the system with third-party services for identity verification and credit checks using REST APIs, implementing circuit breakers with Resilience4j for improved fault tolerance. For monitoring, I set up comprehensive logging using ELK stack and implemented custom Grafana dashboards for real-time loan processing metrics. I containerized the entire application using Docker and deployed it on Azure Kubernetes Service (AKS), implementing horizontal pod autoscaling based on application load. I implemented an automated testing strategy using JUnit, Mockito, and Selenium for end-to-end testing. The system was built with security in mind, implementing OAuth2 authentication, role-based access control, and encryption for sensitive data both in transit and at rest.
Fraud Detection & Security System
At Bank of America, I implemented a real-time Fraud Detection and Security System that monitored banking transactions across multiple channels.
I developed microservices using Spring Boot to process and analyze transaction patterns, implementing machine learning models for anomaly detection.
The system utilized Apache Kafka for real-time stream processing of transaction data, enabling immediate fraud detection and prevention.
I designed a sophisticated event processing pipeline that integrated with multiple data sources, using Cassandra for storing historical transaction patterns and PostgreSQL for managing fraud rules and configurations.
On the front end, I built an administrative dashboard using React, incorporating real-time alerts and interactive visualizations for fraud analysts.
The dashboard included features for managing fraud rules, investigating suspicious activities, and generating comprehensive reports.
I implemented GraphQL APIs to efficiently fetch fraud analytics data and REST endpoints for real-time transaction screening. For enhanced security, I integrated OAuth2 authentication and implemented role-based access control with detailed audit logging.
The system utilized Elasticsearch for log aggregation and Grafana for monitoring system health and fraud metrics. I containerized the application using Docker and deployed it on AWS EKS, implementing auto-scaling to handle varying transaction loads.
I set up comprehensive monitoring using Splunk for transaction logging and alert management. The system included an automated testing framework using JUnit and Cucumber for behavior-driven development, ensuring reliable fraud detection rules.
I also implemented circuit breakers and fallback mechanisms to ensure system resilience during high-load scenarios. One of my key contributions was developing a machine learning pipeline that continuously improved fraud detection accuracy based on feedback from fraud analysts.
The entire system was deployed using a CI/CD pipeline with Jenkins, ensuring rapid and reliable updates to fraud detection rules and algorithms.
Credit Card Management System
At Chase Bank, I developed a comprehensive Credit Card Management System that handled the complete lifecycle of credit card operations.
I designed and implemented microservices architecture using Spring Boot, creating services for card issuance, transaction processing, rewards management, and statement generation.
The system utilized event-driven architecture with Kafka for real-time transaction processing and notifications.
I implemented a hybrid database solution using Oracle for core banking data and MongoDB for customer interaction history and card preferences.
For the frontend, I developed a responsive web application using Angular, featuring interactive dashboards for customers to manage their cards, view transactions, redeem rewards, and handle dispute management.
I implemented real-time transaction notifications using WebSocket connections and integrated with various payment networks through REST APIs.
The system included sophisticated credit limit management algorithms and automated credit line increase evaluations.
I developed GraphQL APIs for efficient data fetching, particularly for complex queries involving transaction history and rewards calculations.
For security, I implemented tokenization for card data, robust encryption mechanisms, and multi-factor authentication.
The system utilized Elasticsearch for transaction search capabilities and Grafana dashboards for monitoring system performance and card usage patterns.
I containerized the application using Docker and deployed it on Azure Kubernetes Service, implementing auto-scaling based on transaction volume patterns.
I set up comprehensive logging and monitoring using Splunk, enabling quick identification and resolution of transaction processing issues.
The system included automated testing using JUnit and Selenium for end-to-end testing scenarios.
I implemented CI/CD pipelines using Jenkins for automated deployments and integrated with Camunda BPM for managing card application workflows.
One of my key achievements was implementing a real-time fraud detection system integrated with the transaction processing pipeline, significantly enhancing security measures.
The entire system was built with high availability in mind, implementing circuit breakers and fallback mechanisms to ensure uninterrupted card services.
Customer Onboarding System
As a Sr. Developer working on the Customer Onboarding System at Bank of America, I developed a comprehensive digital onboarding solution that transformed the traditional paper-based account opening process into a streamlined digital experience. I implemented the backend using Spring Boot microservices architecture, creating separate services for customer verification, document processing, and account creation. For the database layer, I used PostgreSQL to store customer information and MongoDB for document management.
I developed REST APIs for integration with external systems including credit bureaus and identity verification services. The frontend was built using React, featuring a responsive design with step-by-step forms and real-time validation. I implemented Kafka for handling asynchronous events like notification triggers and status updates.
For security compliance, I implemented encryption for sensitive customer data and integrated with the bank's authentication system. I used Camunda BPM to manage complex onboarding workflows, including KYC verification and regulatory checks. The system included document upload capabilities with OCR integration for automated data extraction from identification documents.
I implemented real-time status tracking allowing customers to monitor their application progress. For monitoring and troubleshooting, I set up logging with Splunk and implemented performance metrics using Grafana. The system was containerized using Docker and deployed on AWS, with Jenkins handling the CI/CD pipeline.
One of the key challenges I solved was implementing a feature that allowed customers to save their partially completed applications and resume later, which required careful state management and secure data storage. I also developed a back-office interface for bank staff to review and process applications, including implementing role-based access control and audit logging.
This project significantly reduced customer onboarding time and improved the overall customer experience while ensuring compliance with banking regulations. The system now handles the bank's digital account opening process, supporting multiple product types including checking, savings, and credit card applications.
Corporate Banking Portal
As a Sr. Fullstack Developer at Bank of America, I played a dual role in developing both frontend and backend components of the Corporate Banking Portal. On the backend, I built microservices using Java and Spring Boot, creating APIs for cash management, payment processing, and account services. I designed and implemented the database architecture using PostgreSQL for core banking data and MongoDB for document management, ensuring optimal performance for high-volume transactions.
On the frontend, I developed responsive user interfaces using React with TypeScript, creating reusable components for financial dashboards, payment forms, and account management screens. I implemented real-time data updates using WebSocket connections and integrated with backend services through REST and GraphQL APIs. The UI featured advanced data visualization components for financial reporting and transaction analysis.
I developed authentication and authorization mechanisms using OAuth and JWT tokens, implementing role-based access control for different corporate user profiles. For the payment processing system, I built workflows handling multiple approval levels and integrated with various payment networks. I used Kafka for event-driven architecture, managing payment notifications and balance updates.
Performance optimization was crucial, where I implemented client-side caching strategies and server-side query optimization. I developed features for bulk operation processing, including file uploads for batch payments and automated reconciliation processes. The system included comprehensive audit logging and transaction tracking capabilities.
Working closely with the DevOps team, I containerized the application using Docker and helped set up Kubernetes deployments on AWS. I implemented CI/CD pipelines using Jenkins and set up monitoring using Splunk and Grafana. I also integrated with external systems like SWIFT for international payments and various regulatory reporting systems.
A significant challenge I tackled was developing a flexible entitlement system that could handle complex corporate hierarchies and user permission structures. I also implemented features for transaction scheduling, recurring payments, and real-time forex calculations. The portal successfully streamlined corporate banking operations, providing clients with a modern, secure, and efficient platform for their banking needs.
Financial Document Management System
As a Sr. Fullstack Developer at Chase Bank, I worked on the Financial Document Management System, a comprehensive platform that handles document processing for various financial operations. The system serves multiple user groups including bank tellers, financial advisors, loan officers, and compliance teams, each with specific access levels and functionalities.
I developed microservices using Java and Spring Framework for backend processing, implemented React-based role-specific user interfaces, and integrated both SQL (PostgreSQL) and NoSQL (MongoDB) databases for efficient data management. The system handles various document types including loan applications, account statements, and regulatory compliance documents, with features like OCR processing, document validation, and workflow management.
Key technical implementations included secure document storage using AWS S3, real-time event processing with Kafka, and comprehensive search functionality. I implemented robust security measures including encryption, role-based access control, and audit logging to maintain compliance with banking regulations. The system successfully streamlined document processing workflows while ensuring security and regulatory compliance across all user groups.
ATM Network Management System
As a Sr. Fullstack Developer at Bank of America, I worked on the ATM Network Management System, which monitors and manages ATM operations across multiple regions. The system serves various users including ATM maintenance teams, cash management staff, security personnel, branch managers, and network operations teams.
I developed microservices using Java and Spring for real-time ATM status monitoring, cash level tracking, and incident management. The frontend was built using Angular, providing dashboards for different user roles. Maintenance teams can view ATM health status and service requests, cash management staff monitor cash levels and schedule replenishments, while security teams track suspicious activities and security alerts.
The system uses PostgreSQL for transactional data and Cassandra for handling real-time ATM status updates and events. I implemented REST APIs for standard operations and used Kafka for real-time event processing, ensuring immediate notification of ATM incidents or cash alerts. For deployment, I worked with Docker containers and implemented monitoring using Splunk for tracking ATM performance and security events.
A significant feature I implemented was the automated incident response system, which routes different types of ATM issues (hardware failures, cash shortages, security alerts) to appropriate teams. The system also includes predictive maintenance alerts and cash optimization recommendations based on usage patterns. The implementation helped improve ATM uptime and reduced operational costs while enhancing security monitoring capabilities.
Anti-Money Laundering (AML) System
As a Sr. Fullstack Developer at Chase Bank, I worked on the Anti-Money Laundering (AML) System, which monitors and flags suspicious financial transactions. The system serves compliance officers, fraud investigators, risk analysts, bank auditors, and regulatory reporting teams.
I developed Java and Spring-based microservices that process transaction data through complex rule engines to identify suspicious patterns. The frontend, built with React, provides intuitive interfaces for case management and investigation workflows. The system integrates with multiple data sources using both SQL (Oracle) for customer data and MongoDB for transaction analysis and case management.
I implemented real-time transaction monitoring using Kafka for event streaming, allowing immediate flagging of suspicious activities. The system uses GraphQL APIs for flexible data querying and REST APIs for standard operations. I built automated reporting modules using Python for regulatory compliance reports and implemented workflow automation using Camunda BPM for case management.
Key features I developed included machine learning-based transaction scoring, automated alert generation, and case management workflows. The system includes comprehensive audit logging and document management capabilities for investigation records. We deployed the solution using Kubernetes on AWS, with monitoring through Grafana for system performance and alert metrics. This implementation significantly improved the detection of suspicious activities and streamlined the investigation process while ensuring regulatory compliance.
February 14, 2025
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