Backend and system design
I design APIs and shared business rules with Spring Boot, Kotlin, Java, PostgreSQL, Redis, and Kafka, separating authentication, state ownership, and external failure boundaries.
See the ssu platform evidence →About
I connect ideas to operable services
and document the reasoning.
I study Computer Science at Soongsil University and build backend, data, and AI systems. My implementation boundary includes where data comes from, how a service is deployed, and how failures are observed and recovered.
I prefer defining the problem and constraints before choosing technology. I preserve decisions, rejected alternatives, failed hypotheses, and verified results in code, ADRs, work logs, and troubleshooting records.
Profile
Education and credentials
- Education
- Soongsil University — Computer Science & Engineering
- Credential
- 컴퓨터활용능력 2급 (Computer Specialist in Spreadsheet & Database, Level II)
- Credential
- 정보처리기능사 (Craftsman Information Processing)
- Contact
- seongjuice999@gmail.com · solved.ac ↗
What I can demonstrate
Capabilities backed by projects
Deployment and observability
I operate ARM64 k3s, ArgoCD, Prometheus, Grafana, Tempo, and Loki, and provision AWS infrastructure with Terraform. Verification follows the request into the runtime.
See the operating model →Data and performance
I built idempotent ETL for more than 150,000 public POIs and PostGIS spatial search, validating plans, buffers, tail latency, and result equivalence.
See the Geuneul evidence →Operable AI systems
I connect RAG, agents, and LLMs to products while keeping money, permissions, state transitions, and publication decisions in deterministic code.
See an AI validation boundary →How I work
Working principles
Start with the user and failure cost.
I define the decision a user needs to make and validate the riskiest assumption with the smallest useful experiment.
Treat operations as implementation.
Deployment, observability, security boundaries, and recovery paths are part of done. Work in progress remains labeled as such.
Separate contribution from evidence.
I state my role in team work and publish performance or incident claims with reproduction conditions and limitations.
Make decisions reviewable.
Small changes, API contracts, ADRs, and tests preserve context so a team can understand why a decision changed.
What I am looking for
Backend, platform, or AI backend opportunities
I am looking for an entry-level or junior role where I can turn product problems into server and data structures, own deployment and observability, and convert operational learning into team knowledge.