Staff AI Enablement Engineer

Shape the Future of Privacy Usercentrics is a global leader in data privacy and privacy-led marketing solutions. We believe there is no need for a trade-off between growth and privacy compliance. Our vision is to unlock the potential of data privacy to empower a thriving digital ecosystem. We work with companies to create a healthy balance between data-driven business and privacy-led marketing for every size of enterprise. Our customers build trust with their users through improved transparency and control to drastically improve marketing and monetization, while achieving full privacy compliance. About the Office of AI The Office of AI owns the strategy, governance, infrastructure, and enablement of AI across Usercentrics. We sit within the CTO office and work across all departments. Mission: enable the entire organisation to adopt AI safely, responsibly, and effectively. About the role You are the senior technical owner of AI enablement at Usercentrics: the person who takes the hardest department AI builds, the deepest platform problems, and the technical bar the rest of the enablement track works to. The role has two layers, and we mean both. At the department layer, you do what every AI Enablement Engineer does, prototyping and shipping AI applications for Finance, Legal, HR, Marketing, Customer Success, BI and beyond, but you take the hardest ones yourself and set the pattern the others follow. At the platform layer, you own the infrastructure that makes all of that possible: the LLM access gateway, RAG infrastructure, model operations, evaluation frameworks, and the engineering standards product teams build against. What you would be walking into: a real internal AI platform already adopted across the company, the AI Hub, MCP servers, Claude connector delivery, a skill hub, usage analytics, and low-code automation. The next layer is largely open. A gateway, RAG infrastructure, model operations, and evaluation frameworks are the current candidates, and you would have a strong say in what gets built and in what order. Real adoption already exists, which is a rarer starting point than a blank slate. The role asks for two things at once. You are a deeply technical engineer who can architect and build these systems hands-on, at the hardest end of the department builds and the platform layer both. And you build a technical community: you raise the bar across the Enablement Engineers and beyond through education, mentoring, and reusable patterns. If you only have one of these, this is probably not your role. You will work alongside the AI Enablement Lead, who owns the non-technical adoption pillar (the champion network, AI literacy, and the cross-department use-case pipeline). Your focus is the engineering depth behind that pipeline, from the department app someone is using tomorrow to the platform layer that will still be standing in two years. On the shape of it: this is a small, senior team today, four to five people, and…