multiverse - AI Portfolio Lead
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Requirements
• AI Domain Expertise: You bring a sophisticated background in AI upskilling, fueled by a network of experts that ensures you’re always ahead of the next big shift. You understand the infrastructure and tools needed to support modern AI - generative, agentic and beyond • Product or Curriculum Launch Experience: Proven experience working with a broad cross functional group of stakeholders to launch learning products and their ongoing improvements • Confident Written and Oral Communication at all levels: You switch with ease from talking about the technical specifications of a new learning lab environment, to effectively raising a risk with the SLT on product performance, to convincing a CIO on the ROI your products bring to his business metrics. You actively enjoy thinking about how to influence these different stakeholders • Ability to distinguish between signal and noise: You know how to make stakeholders feel heard whilst holding the line on what is right to prioritise and why. You effectively balance the need to improve learner experience with the practical realities of working with constrained resources • A strong vision for applied learning: you strongly believe in the power of apprenticeship and applied learning models to supercharge the acquisition of data skills and you bring vision and expertise both internally and externally to how to do this effectively • AI enabled practices: you have experience building and using AI workflows to automate research, development and reporting tasks. You are excited about embracing AI to help you spend time on the tasks which most need your expertise • AI Practitioner: you have significant technical proficiency in AI automation tooling and can speak from lived experience in designing learning for these tools • Instructional Literacy: Experience with cohort-based or online content creation, specifically within technical or professional training • Regulatory Knowledge: Experience working within regulated structures (e.g., UK Apprenticeship Levy) is a significant plus.
Responsibilities
• Portfolio Strategy • AI Product Roadmap: Own the development and iteration of a sub set of our AI product offerings by analysing data (both internal and external) to improve net new bookings, customer retention and learner retention • Market Alignment: Validate our assumptions and competitor analysis in the market in partnership with Product Marketing, shaping how we communicate technical value and competitor positioning • Horizon Scanning: Stay ahead of the curve on data and tooling trends to identify new skills development pain points and opportunities • Investment Validation: Support GTM, Finance and our Delivery teams to scope custom data offerings, balancing market potential against the technical investment required • Policy Influence: Support our Policy team to craft compelling responses to consultation requests and consider proactive initiatives to actively shape apprenticeship policy for your area • Product Development, Launch & Iteration • Learning Squad Management and Prioritisation: work collaboratively with stakeholders across the business to create compliant apprenticeship curricula which meet learner and client needs. Use data and insights (qualitative and quantitative) to identify and prioritise opportunities for growth and improvement, including managing the backlog and prioritisation of improvements for wider Learning team members and teams external to Learning • Organisational enablement and readiness: support partners in Delivery, Admissions and Product to assess and enable the readiness of our systems and people to deliver a high quality learning experience • Proactive Risk Mitigation: Identify and escalate risks to all levels in the organisation, including C Suite, to ensure products remain on track to hit quality benchmarks. • Agile Feedback Integration: Establish and lead rigorous feedback loops for your products. You won't just "collect" feedback; you will find effective ways to synthesise what you are hearing from different sources including our own internal delivery teams, learners and clients • Expert Credibility: Serve as the internal and external "voice of the data practitioner," building trust with technical leaders and stakeholders at all levels
Benefits
• Time off - 27 days holiday, plus 5 additional days off: 1 life event day, 2 volunteer days, 2 company-wide wellbeing days (M-Powered Weekend) and 8 bank holidays per year • Health & Wellness- private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership & wellness resources through Wellhub and access to Spill - all in one mental health support • Hybrid work offering - for most roles we collaborate in the office three days per week with the exception of Coaches and Instructors who collaborate in the office once a month
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