AI Asset Manager

Overview

In this AI Asset Manager role you own the development and ongoing management of AI assets that underpin new assessment products and services. You’ll collaborate with AI researchers, developers and stakeholders to turn emerging AI capabilities into practical solutions for learners and educators. You’ll shape the roadmap for AI assets and drive value, innovation and fit-for-purpose delivery. This is a chance to influence AI-enabled assessment at a national education leader and work hybrid across Manchester or Milton Keynes.

Pay / Benefits

• competitive pension scheme
• private healthcare
• generous annual leave
• hybrid working
• ongoing professional development
• flexible working arrangements

Responsibilities

• Define and own the roadmap for AI assets to deliver value and align with long-term innovation strategy
• Collaborate with technical teams, stakeholders and external partners to develop, enhance and manage AI tools, software and IP
• Lead strategic AI initiatives using customer insights and market trends to improve assessment solutions
• Collaborate with cross-functional teams to continuously improve customer value proposition
• Manage strategic AI asset development, delivery and withdrawal projects
• Analyze customer needs and competitive position to inform AI capabilities and product strategy
• Produce evidence-based proposals and business cases for AI tools and services
• Monitor operational performance and inform strategic priorities across AI assets

Key requirements

• Degree-level education or equivalent experience
• Experience managing technology products, AI tools, software assets or digital solutions in a research or innovation environment
• Ability to work with developers, engineers and technical specialists and translate complex concepts for broader stakeholders
• Strong stakeholder management, communication and influencing skills across a complex organisation
• Experience developing roadmaps, prioritising activity and managing multiple projects concurrently
• Analytical and commercially minded approach with data-informed decision-making

• communication
• influencing
• negotiation
• AI development and management in a research/innovation setting
• managing AI tools, software assets and IP
• data analysis and interpretation for strategic decisions

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