AI Engineer (f/m/d)

Clariness is looking for an AI Engineer (f/m/d/) based in Germany. - Full-time; unlimited - About the role: This role is about turning AI and machine learning ideas into reliable, scalable solutions for Clariness' platforms. You will join a collaborative technical environment and work across the AI/ML lifecycle, from understanding a business problem and developing a solution to deployment, monitoring and continuous improvement within the regulated clinical-trial space. As an AI Engineer, you would be responsible for: Designing, building and operating production AI and machine learning solutions, including data pipelines, models and inference services. Developing LLM-powered features using approaches such as retrieval-augmented generation (RAG), agent workflows, tool calling and structured outputs, with a focus on reliability, measurable quality and cost efficiency. Delivering end-to-end machine learning workflows on Databricks, from data preparation and feature development through training and evaluation to batch and real-time deployment. Maintaining quality in production through versioning, evaluation, monitoring and drift detection, and supporting the investigation and recovery of solutions when issues arise. Collaborating with Product, Engineering, Commercial and Operations teams to translate business needs into scoped technical requirements, measurable success criteria and realistic delivery plans, including relevant data and privacy constraints. Contributing to governance-ready data and AI practices covering quality, lineage, access, security, GDPR and responsible AI, including relevant EU AI Act requirements. Working with technical and non-technical stakeholders to explain trade-offs and model limitations, gather feedback and help prioritize improvements based on their potential impact. Reviewing peer contributions, documenting and sharing knowledge, developing reusable components and helping improve our shared libraries and Data & AI platform tooling. We would like you to have:  A degree in Computer Science, Data Science, Statistics, Mathematics or a related field, or equivalent practical experience, together with strong English communication skills at C1 level. 3–5 years of hands-on experience in Machine Learning Engineering, Applied AI, Data Science or a related field, including experience taking at least one AI or machine learning solution from prototype into production. Strong Python skills and practical experience with machine learning frameworks such as scikit-learn, PyTorch or equivalent technologies, along with solid SQL and warehouse or lakehouse experience. Hands-on experience with Databricks, including several of the following: Spark, Delta Lake, Unity Catalog, MLflow or Workflows. Experience evaluating and deploying models beyond the experimentation stage, with an understanding of monitoring, reliability and production quality. Familiarity with LLM application patterns such as RAG, prompt workflows and evaluation, as well as cloud platforms, ideally AWS, and CI/CD practices for machine learning, or the foundations and motivation to develop further in these areas. The ability to independently deliver well-defined AI/ML tasks, collaborate with product and business stakeholders and explain technical trade-offs, model behavior and limitations to non-technical audiences. You may ask now, why should I work for you? Let us give you a few reasons – and you'll learn more during the process. A varied and exciting job with a lot of personal responsibility in an international company, where you can develop and expand your skills. Professional and personal development opportunities - incl. personal development budget. Flexible working hours and mobile working. Regular team events and open feedback culture. A versatile field of activity and challenging projects. A supportive and open company culture, providing the opportunity to collaborate with a diverse and professional team. Impact healthcare by accel