AI Product Owner

Mission:

Frame, prioritize and accelerate AI initiatives across the Quality domain, ensuring that AI opportunities start from validated business needs, generate measurable value and are effectively adopted by Quality teams.

• Main focus: Use case framing, business value, prioritization, adoption, transformation impact.
• Typical outputs: Use case briefs, intake forms, value assessments, roadmap inputs, adoption plans, decision notes.
• Key interfaces: Quality leaders, business stakeholders, AI Team, IT, data teams, delivery teams and change actors.

Primary contribution:

Ensures that AI initiatives start from validated business needs, are prioritized for measurable value, and are adopted effectively by Quality teams.

Key responsibilities:

• Engage Quality stakeholders to identify high-value business problems, pain points, decision bottlenecks, and automation opportunities.
• Frame AI use cases with clear problem statements, impacted users, expected outcomes, value hypotheses, data availability, and constraints.
• Prioritize initiatives based on value, feasibility, scalability, risk, urgency, and alignment with Quality priorities.
• Organize and run business workshops to collect AI opportunity ideas, challenge pain points, structure needs, and frame projects into actionable use cases.
• Drive adoption planning by defining target users, process impacts, change actions, communication needs, and success indicators.

Basic Qualifications:

• Bachelor's Degree in Engineering, Business, Data/AI, Digital Transformation, Quality Management or equivalent field
• 7+ years of relevant experience 
• Languages: Fluent English required; additional languages are a plus in an international environment
• Soft skills: Business acumen, facilitation, stakeholder engagement, strategic thinking, change leadership, communication impact and ability to influence without authority

Preferred Qualifications: 

• Strong understanding of Quality processes, business transformation, AI opportunity assessment, and value framing
• Ability to translate business needs into structured AI use cases without over-specifying the technical solution too early
• Experience organizing and facilitating workshops with business stakeholders to collect ideas, align priorities, and produce concise decision-ready documentation
• Knowledge of the AI delivery lifecycle, including POC, MVP, industrialization, deployment, adoption, and performance tracking
• Solid working knowledge of ML, GenAI, and AI technologies, with the ability to understand their capabilities, limitations, and business applicability
• Curiosity and appetite to stay continuously up to date with emerging AI technologies, market trends, best practices, and relevant use cases