Product Manager

Product Manager – AI Infrastructure & Private AI Solutions Overview We are working with a leading organisation in the AI and infrastructure space that is looking to hire a Product Manager to define and scale a portfolio of AI infrastructure and private AI solutions. This role focuses on GPU-accelerated systems, high-performance networking, storage, and the software stack required to run AI in production environments. You will bridge customer needs with technical delivery, shaping product strategy, roadmap, and go-to-market.

Key Responsibilities Own the product strategy and roadmap for AI infrastructure and private AI offerings Engage with customers to understand use cases, requirements, and constraints (e.g. compliance, latency, cost) Translate AI workloads into clear product requirements (training vs inference, performance, scalability) Define commercial models including packaging, pricing, and service offerings Work closely with engineering and architecture teams across compute, networking, storage, and software layers Create product documentation including requirements, user stories, and acceptance criteria Support go-to-market activities including positioning, messaging, and sales enablement Track product performance using key metrics and continuously improve based on feedback Collaborate with external partners to build integrated solutions and reference architectures Ensure smooth lifecycle management including documentation, upgrades, and support processes Requirements Essential: Experience in product management or a closely related role (e.g. solutions architecture, engineering, technical program management) Strong cross-functional collaboration skills Ability to communicate complex technical concepts clearly Solid understanding of infrastructure and cloud technologies (compute, storage, networking, containers) Customer-focused mindset with experience gathering and prioritising requirements Strong interest in AI and emerging technologies Desirable: Background in data centre infrastructure, cloud platforms, HPC, or AI systems Familiarity with GPU-based environments and AI workload requirements Understanding of private AI architectures (e.g. model deployment, data pipelines, observability) Experience designing or working with on-prem or hybrid infrastructure solutions Knowledge of performance, scalability, and capacity planning Experience working with technology partners and joint solutions