Architected and deployed Java/Spring Boot microservices on AWS powering 100,000+ daily payment transactions while sustaining 99.9% uptime.

Implemented event-driven messaging with Kafka and coordinated distributed transactions using the Saga pattern, reducing end-to-end latency ~40%.

Built an AI-driven search/RCA platform (LangChain + vector DB) to retrieve relevant logs/runbooks, reducing mean time to recovery (MTTR) ~40%.

Improved API performance by tuning PostgreSQL queries and introducing Redis caching, reducing response times ~30%.

Executed JMeter load tests and tuned AWS autoscaling + load balancing to keep p99 latency under 150ms under 50,000+ concurrent users.

Containerized services with Docker and Kubernetes; integrated Prometheus + CloudWatch monitoring to improve observability and enable ~40% faster incident recovery.

Established CI/CD pipelines (GitHub Actions + Jenkins) for automated build/test/deploy, shortening release cycles by [60%] and reducing deployment risk.

Tech stack line: Java, Spring Boot, Kafka, AWS (EKS/Lambda/S3/CloudWatch/IAM), Kubernetes, Docker, PostgreSQL, Redis, JMeter, CI/CD, Prometheus.

Built a real-time research analytics dashboard with Angular Universal (SSR), improving page load time ~40% and strengthening perceived performance for end users.

Designed and deployed a Node.js/Express + GraphQL backend on Kubernetes to support high-concurrency visualization queries for research teams.

Implemented JWT auth and role-based access control (RBAC) to protect sensitive research data and align with university data governance.

Partnered with faculty/research stakeholders to translate complex requirements into interactive dashboards (Chart.js + D3.js), increasing data accessibility ~20%.

Reduced visualization query latency by ~35% via GraphQL query optimization (resolver batching, dataloader pattern), Redis caching strategy, and backend profiling with APM tools.

Improved reliability and deployment repeatability by standardizing containerized delivery on Kubernetes and creating runbooks, cutting onboarding time by ~50%.

Tech stack line: Angular Universal, Node.js, Express, GraphQL, Kubernetes, JWT/RBAC, Chart.js, D3.js.

• Led development of 'Virtual Apprentice' AI-powered educational platform, creating user-friendly interface using Angular, HTML, and CSS with Node.js backend services, serving 500+ potential users in pilot testing

• Designed and implemented RESTful APIs and database integration, enabling seamless user interaction and system integration for educational content management with 99% uptime

• Collaborated with interdisciplinary team of 5+ researchers and developers to design innovative learning solutions, resulting in 40% improvement in user engagement metrics during testing phase

• Presented 'Virtual Apprentice' platform at TEDx UMBC, reaching audience of 200+ attendees and receiving recognition for innovative approach to educational technology

• Conducted comprehensive user research and testing with 50+ participants, gathering feedback that led to 30% improvement in user interface design and functionality

• Developed technical documentation and project proposals that secured $10K+ in additional funding for platform enhancement and expansion

• Applied agile development methodologies and version control systems, maintaining code quality and project timeline adherence with 100% milestone completion rate

Built resilient Java payment orchestration services using Kafka + Saga pattern, ensuring ACID-like consistency across distributed microservices handling 10,000+ daily transactions.

Added robust retries, circuit breakers, idempotency keys, and recovery logic, improving transaction reliability ~45% and reducing failed payment rollbacks.

Refactored Spring Boot services for asynchronous REST communication (CompletableFuture + non-blocking IO), boosting throughput ~30% and lowering inter-service latency.

Developed REST APIs with schema validation, optimistic locking, and concurrency control, improving warehouse inventory accuracy ~25%.

Built automated test suites (Selenium, JUnit, Mockito) in a TDD workflow, reducing manual QA effort ~75% and increasing regression coverage to 85%+.

Served as acting Scrum Lead for a 6-person team, improving delivery velocity ~25% through sprint hygiene, backlog refinement, and Kanban flow optimization.

Added performance monitoring and alerting for payment workflows (Prometheus + Grafana + ELK), reducing incident detection time by ~60%.

Documented integration contracts, idempotency guarantees, retry/backoff strategy, and failure modes, reducing cross-team integration defects by ~40%.

Tech stack line: Java, Spring Boot, Kafka, Saga pattern, REST, Selenium, JUnit, Mockito, TDD, Agile/Scrum, Jira.

Streamlined Oracle → Amazon Redshift data migration (ETL), resolving 200+ data discrepancies and improving overall data quality ~50%.

Built Java-based automation for extraction and transformation workflows, cutting ETL batch processing time ~30% and reducing manual intervention.

Optimized Hibernate queries (index tuning, batch fetch size, N+1 elimination) and resolved memory leaks, reducing system crashes ~40% and stabilizing long-running jobs.

Automated ETL deployments on AWS using Jenkins + Docker, eliminating manual configuration steps and improving pipeline reliability.

Implemented validation checks, reconciliation tooling, and row-count/hash comparison frameworks, reducing migration rework by ~60%.

Coordinated with data owners and stakeholders to define acceptance criteria and formal data contracts, decreasing late-stage defects by ~35%.

Tech stack line: Java, ETL, Oracle, Redshift, AWS, Jenkins, Docker, Hibernate.