This is Adyen
Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition.
For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster.
AI & Innovation Lead, Operations
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.
AI & Innovation Lead, Operations
- 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.
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