Python Developer – Structure, Tests & a Launch-Ready MVP
The role
You’ll work closely with our AI developer and give the codebase a clear structure through small, practical steps—so we can ship safely and keep moving fast. The focus is on codebase structure, testability, and simple CI practices around what we already have. We run on managed services and prioritise a lightweight ops model.
Context
Our MVP has gotten here through focused, fast execution—the features are in place. Now we’re making it robust and ready for release. We’re approaching our first field test and expect roughly a month to MVP. We’ll keep the pace, while prioritising the foundation that makes releases stable and future development easy.
What you’ll do
Split large files into small, focused modules with clear interfaces.
Set up simple automated checks in CI (format/lint/type-check) to speed up reviews.
Add smoke/boundary tests around critical flows so we can refactor safely.
Update the README and jot short decision notes when we change structure.
Get light senior sparring a couple of hours per month on the trickiest refactors (as needed).
Contribute to small features and continuous improvements when the foundation calls for it.
Secondary responsibilities
Partial responsibility for hosting and technical operations—in collaboration with our current setup (e.g., Supabase/Render)—and help keep a simple ops model.
Maintain a view of the system as a whole and contribute to a clean, well-structured codebase.
Develop new/smaller features and ongoing improvements when the foundation needs it.
What describes you
A nose for robust solutions and you help us keep a steady cadence.
You make it easy to build on what we already have—with simple, practical steps.
You help keep the codebase healthy through small, continuous improvements.
Requirements & nice-to-haves
You have
Hands-on Python experience (study, work, or open source) and Git/GitHub.
An interest in structure, testability, and layering in practice—small, frequent improvements.
Nice to have
Supabase, Render.
TypeScript, React, Next.js.
Basic LLM/RAG concepts (langchain/langgraph/langsmith)—AI is primarily owned by your teammate.
Light ops/hosting and simple observability (logging/error tracking).
Practical
Start: As soon as possible (we’re close to the first field test).
Scope (employment): Part-time, student job or internship (newly graduates are welcome) (15–30 hrs/week) by agreement. (Internships can be full-time.)
Language: English; Danish is a plus.
Location: Flexible/remote with short, regular syncs.
Equity can be negotiated for the right match.
How to apply
Send your CV and GitHub link—ideally with an example of a refactor or a small repo where you made the code easier to work with.
