Senior Engineer, Data Engineering

Skills

• Productive AI use cases (beyond PoC)
• Translation of business problems into AI workloads
• Data landscapes in industrial & OT environments
• Integration of AI into existing ERP/MES/PLM systems
• Profitability analysis of AI initiatives
• EU AI Act (risk classes, roles: provider, deployer, GPAI, high-risk)
• AI governance frameworks and risk management approaches
• Documentation, audit and verification obligations for AI systems
• Data governance, data provenance and training data control
• Liability and accountability models in AI ecosystems
• Cloud, HPC and AI platform architectures
• GPU-based training and inference environments
• Compute, storage and network sizing for AI
• Operating models for regulated/sovereign cloud environments
• Understanding of NVIDIA AI stacks (e.g. AI Enterprise, Omniverse - conceptual)