Senior Data Centre AI Software Product Strategy & GTM Lead — Europe
A world-renowned Semiconductor Giant is expanding its Cloud and Data Centre AI footprint across Europe. They are seeking a Senior Data Centre AI Software Product Strategy & Go-To-Market Lead to define and drive their European software strategy for the deployment of cutting-edge AI accelerators, processors, and infrastructure solutions into European data centres.
This role bridges the gap between regional market demands and global engineering—translating customer requirements, ecosystem dynamics, and European regulatory priorities into high-impact product strategy, roadmap inputs, and go-to-market execution.
Key Responsibilities European Data Centre AI Software Product Strategy Define and maintain the European software product strategy for Cloud and Data Centre AI platforms. Represent European software requirements directly to global HQ product management and engineering teams. Translate customer, partner, regulatory, and ecosystem needs into software product requirements, roadmap inputs, product positioning, and GTM messaging. Pinpoint where European requirements diverge from global assumptions—specifically around data sovereignty, privacy, energy efficiency, cloud deployment models, enterprise adoption, AI governance, and public-sector needs. Build compelling narratives for cloud providers, telcos, enterprises, sovereign cloud providers, public-sector customers, ISVs, and system integrators. Capture competitive objections, software gaps, developer needs, and adoption barriers across European engagements.
Go-to-Market Enablement Architect strategies to seamlessly integrate AI accelerators and platform assets into data centres with established single or multi-vendor software stacks. Craft high-value propositions, competitive positioning, technical explainers, launch materials, and sales enablement content. Equip European GTM teams with clear messaging on the company’s Cloud and Data Centre AI software capabilities. Partner with regional marketing and communications teams to support industry events, customer workshops, partner briefings, and thought-leadership initiatives.
Required Expertise Core Background Deep expertise in Data Centre AI and Cloud Software architectures. Proven understanding of how the full software stack is leveraged to deploy and optimise large AI models within data centre environments. Hands-on knowledge of end-to-end AI workload deployment and performance optimisation.
AI Software Platforms Strong knowledge of inference, model deployment, runtimes, SDKs, and developer toolchains. Expertise in AI orchestration frameworks (e.g., Kubernetes-based systems, Ray, v LLM, TGI). Solid grounding in cloud-native AI software stacks, deployment patterns, and data centre operating models.
Data Centre AI Infrastructure Experience across CPUs, GPUs, NPUs, and heterogeneous accelerator environments. Proficiency in Kubernetes-based environments, containerisation, and workload management. Mastery of resource scheduling, bin-packing, and topology-aware placement. Deep knowledge of model serving, compilers, runtime frameworks, memory-aware serving, KV cache optimisation, and multi-model serving. Track record of driving performance optimisation across latency, throughput, and power efficiency.
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