AI Engineering - Intern

GeneralMind; Berlin; Vor Ort; Vollzeit

Jobbeschreibung

GeneralMind builds AI Systems of Action for complex enterprise workflows. We deploy AI employees that automate messy operational handovers across supply chains, processing orders, validating invoices, coordinating suppliers, and handling exceptions directly on top of enterprise systems like SAP or Oracle.

Our platform combines AI agents, operational context graphs, and real transaction data to achieve Autopilot-grade automation in real operational environments. We work closely with leading global companies across manufacturing, retail, and logistics to deploy AI into mission-critical workflows.

About the role

This is not a role where you will triage bugs or sit in on meetings to learn the ropes. We are looking for someone who is already building: shipping personal projects, entering hackathons, experimenting with the latest models, and who wants to do that with a high-caliber team on a real product.

You will work across the full stack (Python backend, Next.js frontend) on features that actually ship. We care a lot about AI; it is central to what we build, not a feature we bolt on, and we want an intern who feels the same way. If you have won a hackathon, placed in a competition, or built something that made people stop and pay attention, that tells us more than your transcript does.

You will be treated like a junior engineer, not a temporary guest. You will get real tickets, real feedback, and real ownership over what you build.

What you will do

Building features

Work across frontend (Next.js) and backend (Python / FastAPI) to ship product features end to end.

Take tickets from scoping to PR: write the code, write the tests, and walk it through review.

Contribute to a codebase where quality is expected, not optional.

AI integration

Build on top of LLMs: prompt design, tool use, agentic workflows, and evaluation, with an understanding of what is happening under the hood.

Contribute ideas on how AI can be applied meaningfully to the problems we are solving.

Stay close to what is shipping in the industry, and bring relevant breakthroughs and tools to the team's attention.

Collaboration and learning

Work directly with senior engineers: pair, review, and get honest feedback.

Ask questions, challenge assumptions, and contribute to design discussions.

Move fast without being sloppy: you know the difference between a quick win and a shortcut that creates debt.

What we are looking for

Currently studying or recently graduated in computer science, engineering, or a related field, or self-taught with a portfolio that speaks for itself.

Builder instinct: you have personal projects, side experiments, or open-source contributions. You build things because you cannot not.

Hackathon or competition track record: you have entered, placed, or won. It tells us you can work fast, make decisions under pressure, and ship.

Full-stack range: comfortable in both frontend and backend. You do not need to be an expert in everything, but you should not be blocked by either side of the stack.

AI-native: you use AI tools daily, understand how LLMs work at a practical level, and have built at least one thing that calls a model and does something useful with the output.

Judgment: you can tell when something is good enough to ship and when it is not.

Curiosity that compounds: you follow what is happening in AI research and tooling, you have opinions, and you bring them.