In a Nutshell

AI only creates value when it meaningfully changes how a business operates. 

As our Manager, AI Productivity Engineer, you will embed directly within business domains to turn prioritised AI use cases into secure, scalable and integrated solutions. You will combine strong technical capability with deep curiosity about how AI can enhance performance across multiple functions, from Finance and People to Sales and Customer teams. 

Working through our AI Ignite governance framework, you will take ideas that demonstrate clear strategic value and convert them into working, production ready solutions. Whether building agentic workflows, deploying enterprise AI applications or integrating tools through robust API architecture, your focus will be on pushing the dial on innovation while ensuring measurable business impact. 

This is not a theoretical AI role. The challenge is integration. Connecting platforms. Embedding AI into live workflows. Ensuring enterprise standards are met. Delivering productivity gains that endure beyond the pilot phase.

Day to Day

• Embed within business functions to identify high friction processes and prioritised AI opportunities 
• Translate approved AI Ignite use cases into defined technical requirements and delivery plans 
• Design, build and deploy AI enabled applications and agentic workflows using enterprise AI platforms 
• Integrate AI solutions into operational systems and enterprise tools through secure API architecture 
• Rapidly prototype, iterate and productionise solutions that deliver measurable productivity gains 
• Redesign workflows to reduce manual effort and cognitive load 
• Partner with Security, Architecture, Engineering and Data teams to ensure responsible and compliant deployment 
• Upskill colleagues and leave sustainable AI capability within the teams you support

About You

• Experience building and delivering AI, automation or software solutions that moved beyond experimentation and created real-world impact, whether in production environments, operational teams or scaled internal use.
• Integration of AI tools or applications into broader workflows or systems (e.g. via APIs, orchestration frameworks or automation platforms), or the ability to clearly articulate how this would be approached.
• Design of AI-enabled workflows, productivity tools or agent-based solutions that meaningfully improved how teams operate.
• A track record of translating ambiguous business challenges into defined requirements, delivery plans and working solutions with clear success measures.
• Understanding of enterprise security, governance and compliance guardrails, and the ability to design responsibly within them.
• Effective collaboration with Engineering, Architecture, Digital or Data teams to embed solutions into complex ecosystems.
• Comfort operating as a hands-on, technically accountable individual contributor with strong ownership from idea to outcome.