Worked on the tolgee-platform repository to deliver a targeted Content Tagging Performance Enhancement, focusing on optimizing backend operations for applying tags to content. Using Kotlin and Hibernate, addressed inefficiencies in the many-to-many mapping between translations and tags, which previously led to excessive database queries and memory bloat. The solution involved root-cause analysis and a patch that reduced the memory footprint, allowing production heap sizing to be tuned down from approximately 10GB to 2GB. Validated in both QA and production environments, these changes improved scalability and responsiveness for large tag sets, resulting in more efficient and stable tagging operations.