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 roles
- Proven expertise in AI solutions development , including understanding of data integration, machine learning pipelines, and AI ethics frameworks
- Strong 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 KPIs
- Fluency in English (written and spoken) for cross-functional stakeholder communication
- Demonstrated ability to manage complex backlogs and prioritize capability-scaling initiatives
Nice 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