Worked on optimizing search payloads for the Tencent/WeKnora repository by refining Elasticsearch queries to exclude the embedding field from search responses. This backend enhancement, implemented in Go, focused on reducing the size of data returned by search-heavy endpoints, which in turn improved response latency and lowered bandwidth consumption. The approach targeted performance bottlenecks by minimizing unnecessary data transfer, thereby enhancing scalability for high-traffic search workloads. Leveraging skills in API development and Elasticsearch, the developer delivered a focused patch that addressed resource usage concerns, resulting in faster and more efficient search operations without altering the core functionality of the existing endpoints.