Developed the S3 Vector Store feature for the spring-ai repository, enabling AWS S3-backed storage of document embeddings and efficient similarity search capabilities. Leveraged Java, Spring Boot, and the AWS SDK to integrate vector database functionality, supporting fast retrieval and association of embeddings with documents. Updated the vector store to version 2.0.0-SNAPSHOT, addressed metadata handling to ensure accurate embedding-document relationships, and enhanced documentation for improved onboarding and usage clarity. Focused on code quality by resolving checkstyle violations and performing code cleanup, resulting in a maintainable and standards-compliant codebase. No bugs were reported or fixed during this development period.