- A degree in computer science, data science, engineering, or a related field.
- Experience designing maintainable, agent-ready engineering environments, including repository structures, coding standards, automated test suites, CI/CD workflows, documentation patterns, and feedback mechanisms that allow software engineering agents to safely generate, modify, review, and maintain code.
- Experience with knowledge graphs, graph-based retrieval, semantic modelling, or ontology-driven knowledge representation is a plus.
- Strong coding skills in Python and experience with robust software engineering practices.
- Practical experience with RAG pipelines, vector databases, embeddings, or fine-tuning workflows.
- Strong understanding of common challenges in AI development (ground-truth evaluation data, monitoring, integration complexity, model drift).
- Experience deploying AI systems in a cloud environment and working with modern ML stacks.
- Familiarity with MLOps, prompt engineering, or LLM-based application design.
- Ability to explain complex AI topics in clear and actionable language to technical and non-technical stakeholders.
- High motivation, ownership mentality, and a strong drive to build impactful AI products.
- Fluency in English; German is a plus.
A culture of growth. With over 50 nationalities represented, we’re proud to welcome people of all backgrounds to our growing community, and we’re always finding new ways to help people feel welcomed and included. Here, you’ll have the tools, training and support you need to work in a way that suits you, learn new skills and reach your potential.
For a career where you can drive our business and shape your future, apply now.