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 field
* Experience building AI Centers of Excellence (CoE) or transformation programs
* Knowledge of insurance-specific use cases (underwriting, claims, fraud detection)
* Familiarity with MLOps practices and AI governance frameworks
* Spanish 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 programs
* Drive Stakeholder Alignment : Partner with business units, data scientists, engineers, and external vendors to gather requirements and ensure technical feasibility
* Manage Scaling Backlog : Prioritize and refine capability-scaling backlog items, ensuring alignment with roadmap and business value
* Champion User-Centricity : Coordinate user research, validate AI solutions against user expectations, and balance IT constraints
* Track Performance : Monitor KPIs (adoption rates, model accuracy, ROI) to make data-driven optimization decisions
* Shape Long-Term Vision : Identify opportunities to scale AI solutions across business units and explore emerging AI applications
* Oversee Documentation : Lead creation of technical guides, integration playbooks, and training materials for seamless solution adoption