related data center offerings. Define European requirements for AI infrastructure software, including model serving, orchestration, workload management, developer tools, runtime environments, compilers, SDKs, containerization, Kubernetes integration, observability, benchmarking, security, and deployment workflows. Develop European messaging around performance, power efficiency, total cost of ownership, software maturity, deployment flexibility, openness, sovereignty … product marketing, or AI platform strategy. Strong understanding of AI software platforms, including inference, model deployment, runtimes, SDKs, developer tools, AI orchestration frameworks (e.g., Kubernetes‐based systems, Ray, vLLM, TGI), and cloud‐native and edge AI software stacks. Experience with data center AI infrastructure, including CPUs, GPUs, NPUs, heterogeneous accelerator ...