Senior Data Engineer (Agentic AI) | f/m/d

ERGO Technology & Services S.A. (ET&S), a member of the Munich Re and ERGO Group, delivers integrated IT and business services internationally, focusing on modern, business-driven technology solutions and supporting insurance processes including finance, operations, and underwriting. The company has offices in Warsaw and Gdansk and promotes a diverse and multicultural environment with global partnerships.

• Fluency in English and German
• Completed degree in computer science, artificial intelligence, or data
• Sound knowledge of GenAI, machine learning, deep learning, relevant algorithms and models, including RAG
• Experience in preparing, cleansing, and enriching data for AI applications
• Very good knowledge of one or more programming languages (preferably Python), particularly AI frameworks (e.g. PyTorch)
• Knowledge of database programming languages such as SQL for managing and querying data
• Experience with tools, frameworks, and technologies for training, deploying, and monitoring AI models, including MLOps practices
• Familiarity with distributed systems and cloud platforms for scaling AI applications (e.g., Azure, Databricks, and Kubernetes)
• Strong ability to identify and analyse data patterns for prediction and decision-making
• Ability to collaborate with interdisciplinary teams and communicate complex technical concepts understandably
• Strong service orientation, excellent teamwork skills, and high commitment to supporting business needs and AI development
• Familiarity with team workflows using git, including creating pull requests and performing code reviews

• Prepare and analyse data from various sources to develop and optimise (Agentic)AI and machine learning models
• Design and standardise effective, scalable AI environments, blueprints, and processes
• Design, implement, and operate software solutions to use structured and unstructured data for automated ML lifecycle
• Develop technical know-how, tools, and methods for (Agentic)AI
• Support operational units in implementing AI models into existing processes and systems
• Design and pilot AI solutions for monitoring and evaluation of AI use case outcomes