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yh4752/README.md

Hi, I'm Yonghyun Kim πŸ‘‹

🎯 AI Backend Engineer · Search / RAG Systems
πŸŽ“ Sejong University, Intelligent Mechatronics Engineering
πŸ‡°πŸ‡· Based in Seoul Β· πŸ‡―πŸ‡΅ Learning Japanese (JLPT N3)


πŸ” What I do

I design and operate production AI search systems end-to-end β€” from incremental ETL pipelines (Airflow + watermark) to hybrid retrieval (Elasticsearch BM25 + Qdrant dense vector), Neo4j-based GraphRAG, and async LLM pipelines (asyncio.Semaphore + ainvoke).

Built and operated these systems during 13 months of military service in the ROK Air Force Data Platform Team.


πŸ’Ό Recent Experience

Republic of Korea Air Force Β· Data Engineering Soldier
Intelligence Information System Management Group, Data Platform Team
Apr 2025 – May 2026

  • πŸ”Ž News Hybrid RAG + GraphRAG Search System β€” Airflow ETL Β· 3-signal Hybrid Retrieval (ES + Qdrant) Β· Neo4j GraphRAG Β· async LLM extraction
  • πŸ—„οΈ Internal Data Hub β€” Kotlin Spring Boot Β· KotlinJDSL Β· event-driven RDB↔ES sync Β· React + TS full-stack
  • πŸ’¬ Real-time Meeting Text Analytics β€” Spring/FastAPI split Β· Kiwi NLP Β· dual-token JWT (key_version + SHA-256/AES-GCM)

πŸ› οΈ Tech Stack

AI / Search
RAG GraphRAG LangChain Elasticsearch Qdrant Neo4j

Backend
Kotlin Spring Boot Python FastAPI PostgreSQL Oracle

Frontend / Ops
React TypeScript Docker Airflow


πŸ“« Contact

πŸ“§ yh47529722@gmail.com
πŸ”— LinkedIn


🚧 Currently building: open-source news hybrid search benchmark with retrieval evaluation (Recall@K, MRR, nDCG)

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