Python Backend Engineer & Engineering Leader | TDD Advocate | AI-Native Engineering
11+ years building backend systems — from large-scale Django products to MLOps / LLMOps platforms, data pipelines, and Kubernetes-based infrastructure. Not just writing code: I find the real problems in the product and resolve them — and I treat test cases as the harness that lets AI agents ship quality at scale.
- 11+ years as a Python backend engineer, now leading a backend team as part lead.
- I write clean, maintainable code and care deeply about software craftsmanship.
- I believe the TDD cycle enhances service reliability and is advantageous for collaboration — I drove the testing culture and dev-process improvements across my team.
- Lately I build AI-Native Engineering environments: pairing AI agents with development workflows — rule files, harness engineering, and spec-driven development (SDD) — to raise both productivity and product quality.
- I lead with a Product Mindset: understanding business requirements and collaborating across roles to create real user value.
- Active communication among colleagues is directly linked to the quality of the product. I really enjoy coffee chats with fellow developers ☕️
📚 I document my learning journey as a 도장깨기 (stamp-collecting) codex at wiki.orchwang.dev — curricula, deep-dives, and article analyses on backend, systems, and AI engineering.
Language
Frameworks
Database
Cloud & Infrastructure
Container Orchestration
AI / MLOps
CI / CD & Docs & Tools
Ray for MLOps — Building and orchestrating scalable ML pipelines on the Ray agent framework for MLOps platforms; cut a 100,000+ Ground-Truth import job by 60%+ via distributed processing.
AI Coding Agents & Harness Engineering — Driving an AI-native workflow on my team: CLAUDE.md-guided agents that run TDD, staged rule files distilled from review history (cut code-review time by 90%+), and spec-driven development integrated with Jira.
