Head of AI Product Operations

You already run your product practice with LLMs, agents, and automated workflows as standard, and now you want the remit to wire that way of working into an entire SaaS business.

As Head of AI Product Operations, you’ll join our client, a global cyber intelligence platform, with a mandate to turn scattered AI adoption into a coherent, compounding product advantage.

This is a leadership role reporting directly to the CPO, with no predecessor and no inherited playbook; you will define what AI product operations looks like and how it scales.

You’ll sit at the intersection of Product, Engineering, Data Science, GTM, and Operations/IT, ensuring AI isn’t just added as features, but embedded into how the organisation discovers opportunities, builds products, ships value, and measures impact.

If you’re already building at the frontier and want to do it at scale, this is your platform.

What You'll Do

As Head of AI Product Operations, you will own the AI product strategy and multi-horizon roadmap, translating the wider product vision into a sequenced agenda of AI capabilities and features across the platform.

• Define the AI product vision and positioning in partnership with the CPO and Product Marketing, giving teams a clear, shared narrative for how AI differentiates the product in the market.
• Hire, lead, and coach a team of product managers focused on AI, shaping a high-performance culture that is rigorous in discovery, fast in delivery, and deeply connected to customer outcomes.
• Design and run AI-native product operations, building the toolchains, agentic workflows, and knowledge layer that connect planning, analytics, design, and communication into one integrated operating system.
• Collaborate closely with Engineering, Data Science, GTM, and Operations/IT to ensure AI initiatives are technically robust, secure and governed, and that launches land cleanly with customers and the field.
• Define, track, and communicate AI product impact metrics, from feature adoption and cycle times to decision quality and commercial outcomes, and use them to guide investment decisions.
• Enable the wider product organisation on AI-native ways of working through workshops, guardrails, documentation, and hands-on support, making AI the default, not the exception, in everyday practice.