AI Engineering Intern
Work on agentic AI systems, end to end.
A paid internship for computer science students in their third or fourth year. You work on the same production systems as the rest of the team, in clearly scoped pieces, at a pace that fits around your studies.
Every piece of work starts with a clear scope agreed before you begin, and everything you ship gets a proper code review.
- LLM orchestration with LangGraph — multi-step agents, tool calling, and the state machines that keep them predictable.
- RAG and vector retrieval — chunking, embeddings, and measuring whether retrieval returns the right thing.
- Evals — deciding whether a change made the system better, with evidence rather than instinct.
- Real-time voice — streaming speech in and out, inside a latency budget a caller will tolerate.
- AWS infrastructure — the deployment path that puts your work in front of customers.
Most of this is ordinary software engineering — clean Python, sensible structure, tests, review, deployments. The AI sits on top of a well-built codebase, and the codebase is the part that has to be right.
What we look for
Strong Python — real software engineering, not just notebooks.
You understand the code you write. AI assistance is fine; shipping code you cannot explain is not.
An AI system you have built — a RAG app, an agent, an LLM tool — that you can walk us through.
Cloud comfort — any cloud counts. A deployed side project is plenty.
Before you apply
Do I need prior AI experience?
You need to have built something with LLM APIs — a RAG app, an agent, a tool — and be able to explain how it works and what you would do differently. Coursework counts. A side project counts. A tutorial you followed without understanding does not.
Is the internship paid?
Yes. We go through the details in the first conversation.
Can I do it alongside my studies?
Yes — it is built for that. Work comes in clearly scoped pieces and you set the pace. If exams get in the way, tell us early and we will adjust the scope. What does not work is going quiet.
Will I get a certificate?
Yes, once you have delivered work that met its agreed definition of done. It comes with a reference we will actually stand behind, because we will have seen your work.
Could it turn into a full-time role?
It can, and we would like it to for the right people. It is not promised — but good work, consistently delivered, makes that conversation very likely.
How to apply
By email, with links to anything you have built.
Mostly you walking us through something you made. Terms are discussed here.
You see the scope and what done looks like before you commit to anything.
Reviewed, tested and running in a product people use.