Senior Software Engineer with AI/ML Skills

About the job

• Exciting and innovative projects for our clients. Depending on the need, we accompany the process with creative workshops, develop proof-of-concepts, and implement the solutions together
• We use a wide range of AI/ML technologies – from classic supervised learning to exploratory GenAI approaches such as Agentic AI or the Model Context Protocol (MCP). Depending on the need, we work with RAG architectures, primarily in the Azure Cloud, but also in other environments or with open-weight models
• Our solutions often build on the Python ecosystem – from machine learning frameworks like PyTorch or scikit-learn to GenAI toolkits like LangChain or LlamaIndex to backend frameworks with FastAPI. We implement MLOps and deployment with Terraform, Docker, Kubernetes, MLflow, and Azure ML
• A wide range of tasks – from initial workshops with clients (our "AI Kickstart" format) through data exploration to the implementation of scalable AI/ML or software solutions
• Continuous learning and ongoing training in AI/ML and software engineering, as well as insights into the various industries of our clients
• Variety and exciting collaboration in internal project teams as well as on-site with our clients
• An experienced and intrinsically motivated team of AI/ML and software engineers

• Several years of experience (at least 5 years) in developing AI/ML applications and/or software development of modern applications
• A completed master's degree in computer science, data science, or a related field
• Very good knowledge of Python and relevant AI/ML frameworks (e.g., PyTorch, scikit-learn) as well as experience with modern backend stacks (e.g., FastAPI)
• Solid know-how in software development, architectures, and technologies: Java and/or .Net, modern web UIs (Angular, React, Vue.js), databases (PostgreSQL, MS SQL, MongoDB, Redis), best practices (DDD, Agile, cloud-native, TDD...)
• Experience with cloud services, especially regarding ML/AI services (preferably on Azure)
• Practical experience in building AI architectures – from classic ML pipelines to complex GenAI solutions like RAG, agentic workflows, or the Model Context Protocol (MCP)
• You are familiar with embeddings, transformer architectures, and prompt engineering
• Strong software engineering skills: ability to write clean, maintainable code – clean code is a given for you
• Experience with MLOps, deployment, and infrastructure – e.g., Docker, Kubernetes, Terraform, MLflow, Azure ML
• Experience working with CI/CD pipelines and GitOps workflows
• Experience and know-how in handling agentic coding tools like Claude Code
• Confident handling of SQL and NoSQL databases and common storage solutions
• Fluent in German and English, both spoken and written