Offer summary

Qualifications:

Bachelor's or Master's degree in Computer Science, AI, or a related field., Experience with large language models (LLMs) and retrieval-augmented generation (RAG)., Proficiency in programming languages such as Python and familiarity with backend development., Strong problem-solving skills and ability to work collaboratively in a team environment..

Key responsabilities:

Design and implement intelligent systems that act, plan, and learn in enterprise environments.

Collaborate with the team to prototype and build agentic systems powered by LLMs.

Implement tools and frameworks for LLM calls and manage multi-turn interactions.

Document experiments and communicate technical decisions effectively.

Job description

About us:

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.

What You’ll Do:

As a AI Engineer, you’ll work alongside experienced engineers and researchers to design and implement intelligent systems that act, plan, and learn in enterprise environments. You’ll contribute to building agentic workflows — autonomous or semi-autonomous AI agents that complete real-world tasks by coordinating tools, APIs, and reasoning steps.

Collaborate with the team to prototype and build agentic systems powered by LLMs and retrieval-augmented generation (RAG).
Help design agents that can interact with enterprise tools (Jira, Notion, internal APIs, etc.) to solve specific user problems.
Implement tools and frameworks to chain LLM calls, maintain memory/state, and handle multi-turn interactions.
Support training, fine-tuning, and evaluation of LLMs on internal and client datasets.
Write production-ready code and contribute to robust backend systems that support real-time AI workflows.
Document your experiments, communicate tradeoffs, and be involved in making technical decisions.

Required profile