Mingyu Park | Backend Developer
UClone - Optimizing Large-Scale Data Search with OpenSearch
Overview
Resolving search performance bottlenecks from growing conversation data and improving AI response quality
Tech Stack
Go
MySQL
PostgreSQL
Redis
OpenSearch
Docker
GCP
Team
Software Engineer Intern
Period
2026.01 ~ 2026.03
Details
- Overview
- UClone is an LLM-based social platform that creates AI clones reflecting a user's persona and uses them to support task delegation and social collaboration.
- Working remotely for a Silicon Valley startup, I was responsible for the service's backend and frontend development as well as cloud infrastructure operations.
- Background
- As conversation data grew, the existing DB-based search hit a performance bottleneck.
- In addition, the limited context that could be injected into the LLM constrained our ability to improve AI response quality.
- Solution
- Built an OpenSearch cluster and migrated the existing DB search to it, improving search response times.
- Designed an embedding pipeline for conversation data and introduced vector indexing, enabling more context to be retrieved and injected.
- Additional Contributions
- Developed full-stack (web and app) features, including a Go server, and operated the production servers.
- Built a GKE-based load balancer and integrated and optimized LLM APIs to reduce fixed costs.
- Gained experience with agile, daily-standup-driven development while working remotely with a Silicon Valley company.