We are on a mission to pioneer the world’s next era of play. As we grow across Europe and Latin America, we’re building The Playstack - the technology powering the next generation of sports, gaming, and fan experiences. Join us, and help make it the most widely used platform in the world From operations, to marketing, to product, we are looking for talented people who will shape how millions of customers play, watch, and connect every day.What The Role InvolvesAI Learning Strategy & EnablementPartner with business leaders to identify AI capability gaps and learning prioritiesBuild and deliver scalable AI learning programmes, roadmaps, and enablement initiativesSupport enterprise-wide AI adoption through practical, workflow-based learning solutionsCreate toolkits, playbooks, and resources that help employees apply AI effectively in their rolesLearning Experience DesignDesign engaging digital and blended learning experiences focused on AI capability developmentDevelop role-based learning pathways across workshops, self-paced learning, peer learning,



and live sessionsCurate content from internal experts, external vendors, and digital learning platformsContinuously improve learner experience, engagement, and accessibility across learning solutionsCommunity & Programme DeliveryBuild AI Champion networks, communities of practice, and peer learning initiativesLead end-to-end delivery of AI learning programmes, including planning, coordination, vendor management, and implementationMeasure learning impact using analytics, learner feedback, and adoption data to continuously improve programmesWhat We Are Looking For8+ years' experience in Learning & Development, Talent Development, or Organisational DevelopmentStrong hands-on experience driving AI enablement, AI capability development, or AI adoption initiatives within organisationsExperience designing practical, role-based, or workflow-based AI learning solutionsStrong background in instructional design, digital learning, and

📌 AI Learning Partner (Madrid)
🏢 Super
📍 Madrid