Senior Engineering Manager, AI

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.

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.

We are looking for a senior leader to own Office of AI delivery end to end, across two pillars. The platforms and tooling our engineers build on, and the adoption of AI by business users in every department. One owner, both halves.

That means two kinds of outcomes, and we care about both.

For business users: measurable AI adoption in Finance, Legal, HR, Marketing, Customer Success, BI and beyond, tracked on each function's own KPIs rather than on activity. Real use cases in production that people use daily, delivered with those teams rather than handed to them.

For engineers: internal AI platforms and tooling that make an 80-plus person engineering organisation measurably faster and safer.

This is an internal-facing role. You are not building the product we sell. You would lead a small, senior team: a staff AI platform engineer, an AI GRC engineer, 2 AI enablement engineers, and an AI enablement lead. They own the build depth, so you set direction, interrogate the work, and own the outcomes rather than writing the platform yourself.

A lot is already living on both sides. On enablement, a company-wide programme with an active champion network in every department, AI literacy work, and a cross-department use-case pipeline delivering into production. On platform, an AI Hub, MCP servers, Claude connector delivery, a skill hub, AI usage analytics, and low-code automation. The team has moved quickly and is upskilling continuously, which is the only realistic way to work in this field.

What comes next is deliberately open on both sides. Growing the enablement function is one direction, a deeper platform layer another, with an LLM access gateway, RAG infrastructure, model operations and evaluation frameworks as current candidates. But AI moves faster than any roadmap holds, and a real part of this role is judging what is worth doing next rather than executing a list we hand you.

You would shape the roadmap, not inherit it.

The role asks for three things at once, and we mean all three. You are a people leader who runs a mixed technical and non-technical organisation. You have the technical credibility to hire, grow, and challenge engineers at staff level and above, and you expect design feedback from every engineer on the team, not just the most senior. And you deliver AI to business users with measurable outcomes, not activity.

If you only have two of these, this is probably not your role.

The AI Enablement Lead, who owns the adoption pillar day to day, reports into this role alongside the engineers. The weighting is toward enabling business users, with the platform work delivered through your team.

On the shape of it: this is a small, senior team today, four to five people, with a company-wide champion network alongside it. We intend to grow both sides, engineering and enablement, and you would help define what that…