AI & Automation Lead

Job Description

The AI & Automation Lead is responsible for leading the AI & Automation chapter within the Data & AI function and owns the company-wide AI and automation portfolio. Reporting to the Chief Data Officer, this role drives the delivery of AI agents, generative AI solutions and machine learning models that create measurable business value across the organization. The role sets standards for generative, agentic and predictive AI while ensuring the safe, compliant and responsible use of AI technologies. Acting as the senior AI authority, the AI & Automation Lead partners with business leaders and technology stakeholders to identify, prioritize and scale high-value AI opportunities. Success is measured through business value realization, adoption of AI solutions, operational excellence and the development of a high-performing AI and ML engineering organization.

• Information Technology
• Utrecht
• Full-time
• Netherlands
• A pre-employment check can be part of the recruitment process.

• Lead, develop and scale the AI & Automation chapter, including AI Engineers and ML Engineers, ensuring capability growth, talent development and effective squad allocation.
• Own the company-wide AI and automation portfolio by identifying, shaping and delivering AI and machine learning use cases with business stakeholders and Product Managers.
• Define and maintain standards, governance and best practices for generative AI, agentic AI and machine learning across the Data & AI function.
• Lead the development and deployment of AI agents, generative AI solutions and machine learning models, ensuring scalability, reliability and business impact.
• Drive responsible AI practices, including governance, transparency, compliance and adherence to AI regulations and security requirements.
• Build AI capability across the organization through stakeholder engagement, education, knowledge sharing and community development.

Qualifications

For this role as an AI & Automation Lead, we're looking for someone who has the following skills and experience:

• Master’s degree in a quantitative field such as Computer Science, Statistics, Mathematics, Artificial Intelligence or a related discipline.
• Extensive experience delivering AI, generative AI and machine learning solutions into production, including leadership of AI, ML or Data Science teams.
• Deep expertise in machine learning, statistical modelling, data science methodologies, AI engineering and advanced analytics.
• Strong experience with generative AI technologies, agent development platforms, vector search technologies, MLOps practices and the Microsoft Azure ecosystem.
• Proven ability to translate business needs into AI solutions while influencing and engaging stakeholders up to executive level.
• Strong understanding of responsible AI, AI governance, regulatory requirements and emerging AI trends and technologies.