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