About the Role
This role focuses on moving beyond isolated pilots and volunteer-led activity, and building a more deliberate approach to re-engineering work through AI, automation, and better operating design. This role will lead that for Ops. It will set the direction for what an AI-native, and highly leveraged operations model should look like, help identify where the biggest opportunities sit, and create the structure that allows domain-owned use cases to turn into real outcomes. Domain leads will remain accountable for the impact delivered in their own areas. This role exists to bring the thought leadership, technical credibility, outside-in perspective, and driving force needed to help make that happen across the function.
Responsibilities
- Set the AI and innovation direction for Operations, with a clear view of what will create the most meaningful step change in customer experience, productivity, quality, and scalability.
- Work with the domains to identify and prioritise the use cases that matter most, based on business value, feasibility, and readiness.
- Lead the central Ops innovation model, including the structure, ways of working, and foundations needed for domain-led re-engineering to succeed.
- Lead a small team of Forward Deployed AI specialists to turn ideas into real, scalable solutions.
- Build credibility for AI across Ops through clear thinking, practical examples, and a strong view of where the real value is and where the risks are.
- Stay current on the AI landscape, emerging patterns, and market developments, and translate that into practical implications for how Ops should evolve.
- Work with central business enablement and capability teams so that new capabilities landing across the company are connected to Ops needs, and the right upskilling happens as use cases scale.
- Represent Operations in central engineering, making sure that Ops priorities are well understood, well framed, and well supported.
- Track progress and value delivered, and keep the focus on outcomes rather than activity.
What good looks like
- Ops has a clear and credible point of view on where AI should and should not be applied.
- The Domains have better clarity on where to focus and what will drive the biggest outcomes.
- High-value use cases move fast from idea to implementation.
- The relationship between Ops and central engineering is stronger, with clearer translation between operational needs and technical delivery.
- AI adoption in Ops is deliberate, practical, connected to real workflow improvement.
- We build scalable solutions that drive meaningful outcomes.
- Teams are better equipped to work differently as new tools and workflows land.
What you bring
- Strong operational judgement. You understand how real work happens, where friction sits, and what it takes to redesign workflows in practice.
- Enough technical depth to have credibility with engineers and technical partners. You do not need to be the hands-on builder for every solution, but you do need to understand architectures, trade-offs, risks, and what good looks like.
- Deep curiosity in AI and adjacent technology. You naturally keep up with the space, understand where the market is moving, and can separate substance from hype.
- The ability to turn ideas into outcomes. You can move from concept to prioritisation to implementation, and you know how to avoid getting stuck in pilot mode.
- Strong executive presence. You can command respect with senior stakeholders, challenge constructively, and represent Operations well in cross-functional discussions.
- A practical, creative, solution-oriented mindset.
- Long-term thinking. You can look beyond the next pilot or tool and help shape the foundations for where Ops needs to go over time.
- Strong cross-functional instincts. You are comfortable working across operations, engineering, data, product, enablement, and capability teams.
Who you are
- Led meaningful transformation in an operations or service environment.
- Built or scaled AI, automation, or digital workflow improvements beyond small experiments.
- Worked closely with engineering or technical teams and can hold your own in those conversations.
- Influenced senior leaders and moved cross-functional agendas forward without relying only on formal authority.
- Helped shape operating models, governance, or delivery mechanisms that made change more repeatable.
- Worked in an environment where pace, ambiguity, and practical execution all mattered.