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Development and implementation of production-ready AI applications (machine learning, GenAI, LLM-based systems)
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Transition of models into scalable, production systems (end-to-end: from exploration to deployment)
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Design and integration of AI services, APIs, and workflows into existing system landscapes
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Conceptualization and implementation of modern AI architectures (e.g., RAG, feature pipelines, model orchestration)
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Implementation of end-to-end solutions on Azure and Databricks (data, models, deployment)
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Development and operation of data and model pipelines (training, inference, monitoring)
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Use and integration of modern AI tools (e.g., Microsoft Copilot, GitHub Copilot, LLM platforms)
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Ensuring performance, scalability, and maintainability of solutions
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Close collaboration with business units to identify and implement AI use cases