• Backend Developer with a background in data analysis and system development
• Interested in backend reliability, distributed systems, LLM application operations, and production incident analysis
• Experienced in developing and operating services with Python/Django, Java/Spring Boot, PostgreSQL, Redis, Docker, Kafka, and Azure

Languages & Frameworks

DevOps & Tools

• 💼 BuiltOn (2022.03 ~ 2023.06 / Data Analyst)
• 💻 SeeSo (2025.06 ~ 2025.07 / Backend Intern)
• 🏢 Samil PwC AC (2025.08 ~ / Software Engineer)

🏆 Awards

• 2024 KDT Hackathon / President’s Award from the Korea Skills Quality Authority
• KB IT's Your Life 5th Cohort / Outstanding Trainee
• Samil PwC 2026 AI Innovation Challenge / Merit Award

• Redis / Celery incident response
  Investigated a P1 Redis I/O incident on large file uploads and improved task-queue reliability by tuning Redis persistence and separating Celery broker/result-backend responsibilities.

• Celery memory optimization
  Analyzed Celery thread-pool memory retention with tracemalloc, identified multiple leak paths, and restored RSS baseline behavior for Kubernetes HPA scale-down.

• Vertex AI latency optimization
  Reduced cross-cloud LLM call latency by introducing HTTP connection pooling with requests.Session and aiohttp.ClientSession keepalive.

• Langfuse observability setup
  Built and troubleshot a self-hosted Langfuse v3 observability pipeline with MinIO, Redis, workers, and ClickHouse.

Calendar-based scheduling service for sharing availability and coordinating meetings.
🔗 Deploy 🔗 GitHub Repository

• Built a group schedule coordination service where participants can select available dates on a calendar
• Supported simple date, place, and menu voting through a shared link
• Improved SEO with structured metadata, sitemap, robots.txt, and crawler-friendly pages
• Added internationalization(i18n) support by separating UI messages and removing hard-coded Korean text
• Designed for lightweight deployment and GitHub Pages-friendly/static-friendly presentation

MSA-based running platform built with Spring Boot, Kafka, Redis, and Docker.
🔗 GitHub Repository

• Built an all-in-one running platform for runners, crews, and race participation management
• Developed backend features for race application and crew/community domains
• Applied Kafka-based Saga Pattern to manage distributed transactions across microservices
• Used Redis to manage Saga state and maintain consistency between services
• Containerized services with Docker and designed the system around MSA architecture