Data & AI Product Owner

About the role

About CERTANIA CERTANIA is a leading international TIC platform ( Testing , Inspection , Certification ) and scientific advisory group . We unite specialized companies under one roof , combining local entrepreneurial strength with shared capabilities , operational excellence, and a scalable group architecture . Our ambition is to build a powerful, data-driven organization that creates sustainable value through integration , professionalization , and measurable performance improvement . Role Objective The Data & AI Product Owner is responsible for building and scaling CERTANIA's reusable Data & AI product ecosystem across the group . The role owns the roadmap for AI Services , acts as product owner for the Fabric data platform , orchestrates the API and data layer , and drives end -user adoption through Langdock and workflow automation . This is not a pure coordination or advisory role . It requires a hands -on builder mindset , deep technical understanding , strong product ownership , and the ability to lead change across a decentralized , multi- entity organization . The goal is to turn individual data and AI ideas into scalable , reusable capabilities that create tangible business impact across CERTANIA. Key Responsibilities 1. Data & AI Product Ownership Own the vision, roadmap, backlog, and prioritization for Data & AI products and capabilities across the group. Translate business needs into clear product requirements, technical scope, and implementation priorities. Identify use cases that can be built once and reused across multiple portfolio companies and functions. Balance value, feasibility, scalability, and adoption potential in all prioritization decisions. Act as the bridge between business leadership, data teams, IT, and external partners. 2. AI Microservices and Platform Enablement Shape and manage a portfolio of reusable AI microservices that can be made available to everyone in the CERTANIA group. Define functional requirements, usage patterns, and governance for AI-enabled services. Work closely with engineering and architecture teams to ensure services are scalable, maintainable, secure, and easy to consume. Support the industrialization of AI capabilities from prototype to production-ready service. Promote standardization and reuse rather than isolated one-off solutions. 3. API and Data Layer Orchestration Work with the API and data platform layer as the integration and intelligence backbone of the CERTANIA ecosystem. Ensure data sources, systems, and AI capabilities are connected through robust and reusable interfaces. Bring a strong understanding of data structures, data models, pipelines, and platform architecture. Collaborate with architects and engineers on solutions built on Microsoft Fabric, Databricks, or comparable platforms. Challenge technical designs with a strong understanding of business impact, scalability, and maintainability. 4. AI Business Transformation Projects Identify and structure high-value AI opportunities with clear business relevance. Ensure every AI initiative is treated as a business transformation project, not only as a technical pilot. Lead initiatives from idea through proof of concept, validation, rollout, and adoption. Define success criteria, change impacts, operating requirements, and scaling plans. Ensure solutions move beyond experimentation into durable, operational use. Build the transition path from pilot to standardized group capability. Make sure each initiative has clear business ownership and a named change lead in the company, or additional external change support where needed, to secure adoption of the new AI-enabled process. 5. Langdock Usage Analysis and Optimization Analyze Langdock usage across CERTANIA to identify recurring patterns, common use cases, and adoption trends. Identify opportunities to create reusable agents and workflows for broader group-wide use. Optimize usage patterns with a view to value creation, efficiency, and budget control. Support the design of automated workflows that connect users, data, APIs, and AI capabilities. Enable teams across CERTANIA to use Langdock effectively in their day-to-day work. Measure usage, adoption, and business value to continuously improve deployment, impact, and cost efficiency. 6. Change Management and Adoption Drive stakeholder alignment and manage the organizational impact of data and AI initiatives. Develop rollout, communication, training, and enablement concepts for new capabilities. Support adoption across portfolio companies, central functions, and leadership teams. Ensure users understand, trust, and actively use the tools and services provided. Address change resistance with clear communication, practical enablement, and visible business value. 7. Communication and Executive Presentation Prepare high-quality management presentations, business cases, and decision materials. Communicate complex data and AI topics in a structured, concise, and visually compelling way. Support leader