Backend Engineer · Java / Spring · AI Runtime · Cloud & Distributed Systems
Building reliable backend services and practical tools, from AI evaluation pipelines to native macOS utilities.
| 50K messages | ~40 / sec | 10s → 1s |
|---|---|---|
| Queue preparation reduced from 2 hours to 1 minute | Email delivery throughput with Amazon SES | Java Lambda cold start with SnapStart |
- Backend systems for AI interviews and evaluations, including LLM pipelines, durable job processing, and multi-tenant data workflows.
- Event-driven services and cloud operations across AWS, Kubernetes, Kafka, and GitOps delivery.
- AI applications with Spring AI, LangChain4j, OpenAI models, and speech-to-text / text-to-speech.
- Local-first desktop tools, browser utilities, and native macOS integrations.
- Open-source fixes and systems work in Rust, process memory access, and macOS tooling.
- VHS — Fixed GIF output not being generated after recording; merged upstream and included in v0.12.1. (Issue #787, PR #788)
- CXX — Fixed
cxx-buildfailures when shared-header paths cannot be written or linked; included in 1.0.202. (PR #1760) - FileBrowser — Fixed valid parallel uploads being interrupted by per-file inactivity timeouts; merged upstream and included in v2.0.7-beta. (PR #2950)
- Wuma Tracker — Added native macOS tracker support with a Mach-based process-memory backend and shared Windows/macOS process abstraction. (PR #6)
Explore technologies by category
- GitHub: github.com/gudcks0305
- Blog: velog.io/@gudcks0305




