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Builds, runs, and continuously improves Sparda Bank Hannover's internal, scalable AI platform and develops bespoke AI applications — from classical ML forecasting models to LLM-based agents — plus governance standards for in-house AI development. Core stack: Python, Git/CI-CD, Databricks, Azure, RAG, vector databases, and MCP.
Builds, operates, and continuously improves a scalable Databricks-based data lake and data engineering environment at a German bank, developing robust ETL/ELT data pipelines, ensuring data quality, and working with data scientists to deliver data products for AI and generative-AI (RAG) use cases.
Builds, runs, and continuously develops Sparda Bank Hannover's internal AI platform, creating ML and generative AI solutions (LLMs, RAG, AI agents) and setting standards and governance for in-house AI development. Core stack: Python, Git/CI-CD, Databricks, and cloud (ideally Azure).
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