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