Tung Lam tunglambk

AI Engineer · Python · LLM Systems · Open Source Contributor

`> whoami`

I'm an AI Engineer who enjoys understanding how systems behave beneath the abstraction layer.

My interests sit around LLM systems, Python, backend engineering, and production AI. I like reading unfamiliar codebases, reproducing real bugs, tracing them to their root cause, and turning that understanding into small, focused, well-tested fixes.

Right now, I'm intentionally spending more time contributing to the open-source Python ecosystem.

Open Source Mode

Note

I'm currently focusing on real issues in established Python projects: bug fixes, regressions, edge cases, tests, and framework internals.

`debug`

Reproducing tricky bugs
Root-cause analysis
Edge cases and regressions
Understanding framework internals

`fix`

Small, maintainable changes
Regression coverage
Preserving existing behavior
Clear validation before submitting

Open Source Contribution Footprint

_{Generated from my public upstream pull requests and refreshed automatically.}

Latest Open-Source Pull Requests

CS-SI/eodag — #2320 feat(cli): add collections list output formats and id-only default · [merged]
pyjanitor-devs/pyjanitor — #1681 [PERF] Avoid materializing not-equal pairs for keep first or last · [open]
sxzz/ast-explorer — #295 fix: remember parser options · [open]
vitalik/django-ninja — #1757 Use real HttpRequest objects in TestClient · [merged]
yargs/yargs — #2576 fix: complete negated boolean options after --no- (fix #2254) · [closed]

_{This section is kept up to date automatically by GitHub Actions.}

Engineering Focus

`AI systems`

Large Language Models
Retrieval-Augmented Generation
Agentic AI
LLM evaluation
AI system architecture
Production AI reliability

`software engineering`

Python ecosystem
Backend frameworks
API design
Testing & debugging
Distributed systems
Open-source development

Toolbox

`AI / LLM`

`Python / Backend`

`Systems`

How I Solve Problems

Where I'm Heading

`understand → fix → test → contribute`

Build things. Break assumptions. Fix the root cause. Contribute back.

_{AI Engineering · LLM Systems · Python · Open Source}

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