Description

Our mission is to supercharge IT enterprise organizations with custom AI solutions. Headquartered in the heart of Munich with a hub in Lisbon, we’re a team of builders, dreamers, and problem-solvers tackling some of the most exciting and complex challenges in AI native development adoption.

We operate on speed, adaptability, and extreme ownership. That means we move fast, stay flexible, and take full responsibility for our impact. Our clients trust us because we don’t ship generic tools — we embed AI into real-world enterprise workflows with precision and empathy.

As an intern or recent grad, you’ll work closely with senior engineers to build and test agentic workflows — AI systems that go beyond chat to actually execute complex tasks by interacting with APIs, tools, and data sources.

You’ll:

• Build early-stage prototypes of LLM-powered agents that complete tasks across enterprise tools like Jira, Notion, GitHub, and internal APIs.

• Design step-by-step flows where AI can reason, retrieve info, call functions, and complete actions autonomously or with minimal user input.

• Help evaluate open-source agent frameworks like LangChain, CrewAI, or AutoGen, and contribute to building internal tools from scratch when needed.

• Assist in prompt engineering and retrieval-augmented generation (RAG) setups to make agent behavior more reliable.

• Be part of regular team reviews and brainstorms — sharing learnings, debugging complex flows, and pushing ideas forward.

Requirements

You’re curious about how far AI can go beyond chat — and how it can actually get things done in real environments. You love solving problems and want to learn from a hands-on, experienced team.

• Proficiency in Python and some experience with LLM APIs (OpenAI, Claude, Hugging Face, etc.).

• Interest in AI agents and how they interact with external tools or APIs.

• Basic understanding of prompt engineering and chaining logic (even if just from projects or tutorials).

• Eagerness to learn, build, and iterate fast. You’re not afraid of diving into docs, debugging, or pair programming.

• Strong communication skills and the ability to explain your thought process clearly.

• Experience with tools like LangChain, AutoGen, or CrewAI.

• Familiarity with FastAPI, Flask, or building simple REST APIs.

• Worked on a side project or academic project using LLMs or automation agents.

• Understanding of vector stores or semantic search.

• A front-row seat to the next generation of applied AI — building real agents for real enterprises.

• Mentorship and feedback from seasoned AI engineers.

• The chance to ship something useful and visible — not just academic experiments.

• A collaborative, no-ego environment where speed, learning, and ownership are everything.