Take your career to the next level with Amaris Consulting as an AI Product Owner. Become part of an international team, thrive in a global group with €800M turnover and 1,000+ clients worldwide, and an agile environment by planning the kickoff and follow-up on projects. Join Amaris Consulting, where you can develop your potential and make a difference within the company.WHAT WOULD YOU NEED? ✍️Must Have:+4–6 years of experience as a Product Owner or in equivalent technology leadership rolesProven expertise in AI solutions development, including understanding of data integration, machine learning pipelines, and AI ethics frameworksStrong background in insurance or financial services sector (domain knowledge essential)Mastery of Agile methodologies (Scrum/Kanban) and tools (Jira, Azure DevOps)Exceptional analytical skills to translate business needs into technical requirements and KPIsFluency in English (written and spoken) for cross-functional stakeholder communicationDemonstrated ability to manage complex backlogs and prioritize capability-scaling initiativesNice to Have:Advanced degree in Computer Science, Business Administration, or related fieldExperience building AI Centers of Excellence (CoE) or transformation programsKnowledge of insurance-specific use cases (underwriting, claims, fraud detection)Familiarity with MLOps practices and AI governance frameworksSpanish proficiency (valuable for European stakeholder collaboration) WHAT WILL YOU DO? Define AI Strategy: Collaborate with Business Innovation teams to refine and communicate the AI vision for enterprise-wide transformation programsDrive Stakeholder Alignment: Partner with business units, data scientists, engineers, and external vendors to gather requirements and ensure technical feasibilityManage Scaling Backlog: Prioritize and refine capability-scaling backlog items, ensuring alignment with roadmap and business valueChampion User-Centricity: Coordinate user research, validate AI solutions against user expectations, and balance IT constraintsTrack Performance: Monitor KPIs (adoption rates, model accuracy, ROI) to make data-driven optimization decisionsShape Long-Term Vision: Identify opportunities to scale AI solutions across business units and explore emerging AI applicationsOversee Documentation: Lead creation of technical guides, integration playbooks, and training materials for seamless solution adoption