Spearheaded the development of an AI-powered conversational agent at the University of Maryland, Baltimore County, designed to assist parents in tracking their children's developmental milestones.Integrated Natural Language Processing (NLP) models like BERT and spaCy to enhance the agent’s context-awareness and semantic understanding, leading to a 25% improvement in response accuracy.Architected a robust intent recognition pipeline, leveraging machine learning techniques to ensure real-time responses and seamless user interaction.Implemented secure communication protocols, including OAuth and TLS, to ensure the privacy and security of sensitive data, aligning with industry standards such as HIPAA.Applied Agile and Test-Driven Development (TDD) methodologies, developing automated test scripts to validate the agent's functionality, reducing potential issues by 30% across the SDLC.Conducted extensive user testing and performance evaluations, improving the agent's user engagement metrics by 40%.Collaborated with interdisciplinary teams to ensure the successful deployment and continuous refinement of the system,preparing findings for academic publication.

Spearheaded the development of microservices using Java 8/11, Spring Boot, Hibernate, and REST APIs, achieving a modular, scalable, and efficient architecture.Engineered integration solutions for MySQL, PostgreSQL, and NoSQL databases, utilizing complex SQL and optimized ORM queries to enhance data handling and performance.Designed and implemented ETL processes with AWS Glue, facilitating the extraction, transformation, and loading of data from AWS S3 into Redshift, thereby improving data accessibility for analytics.Automated CI/CD pipelines using Jenkins and GitLab CI, deploying Docker containers within Kubernetes environments to enable faster and more reliable software releases.Migrated legacy systems to AWS cloud infrastructure (EC2, S3, RDS), utilizing AWS Glue for ETL tasks to ensure seamless data transformation and processing within the AWS Data Lake.Developed a comprehensive data quality framework and leveraged AWS CloudWatch for monitoring, ensuring data accuracy and reliability across all pipelines.Implemented fault tolerance in microservices architecture using Eureka, Ribbon, and Hystrix to enhance system resilience.Optimized microservices performance through the use of Redis, Kafka, and RabbitMQ, achieving a 40% reduction in latency.Collaborated closely with frontend and DevOps teams to integrate microservices and streamline API interactions.Created test automation suites with JUnit, Mockito, and Gatling, achieving an impressive 85% code coverage verified by Jacoco.Managed version control using Git and contributed to GitFlow, fostering efficient collaboration across teams. Automated infrastructure provisioning with Terraform, enhancing scalability and operational efficiency.

Contributed to the development of an enterprise-level banking application using Java and Spring on server-side Linux, Unix, and Windows systems, focusing on RESTful web services within a microservices architecture.Led the design and implementation of several CI/CD pipelines through Jenkins for Java applications, and assisted in the setup and configuration of AWS environments, including VPCs, EC2 instances, S3 buckets as required by the migration plan.Resolved 10 weekly tickets on Jenkins and Gerrit, improving system uptime by 15% and reducing CI bottlenecks. Implemented IaC with Terraform, using modules and state files, reducing deployment time by 30%.Engineered API design and implemented security improvements, reducing incidents and enhancing overall systemperformance. Utilized Kafka’s scalability, boosting system resilience, and performance and handling 50% more transactions per second.Worked in Agile, collaborating with teams to meet tight deadlines and ensuring project alignment and client expectations. Deployed SonarQube for comprehensive code quality checks in Java projects, implementing static analysis to identify bugs,vulnerabilities, and code smells early.