Lead AI Validation & Governance (GenAI & ML)

In this role you lead AI validation and governance across traditional ML and GenAI/agentic AI, shaping the group’s model risk framework. You provide independent oversight through the full AI lifecycle and stay hands-on with design, validation, and testing. You work with data scientists and engineers to build reusable governance and monitoring tooling, ensuring robust, compliant AI in business-critical contexts. This position blends strategic governance with technical delivery in a regulated environment, offering impact at scale.

• Smart working and flexible hours
• Corporate welfare system
• Meal vouchers
• Supplementary health insurance
• Wellbeing initiatives
• Training and development

• Perform independent validation and challenge of AI/ML and agentic/Generative AI systems across the full lifecycle, including data quality and performance metrics
• Align validation practices with regulations (e.g., EU AI Act) and internal guidelines, translating requirements into processes and controls
• Identify key risks (bias, explainability, compliance) and define validation controls and mitigations
• Define and implement continuous monitoring and alerting for production AI systems (drift, emerging GenAI risks)
• Ensure ongoing lifecycle compliance, including periodic re-validation
• Design reusable functionalities to enable scalable governance and monitoring
• Collaborate with data scientists, engineers, and stakeholders as a second line of defense
• Maintain robust documentation and support audits, contributing to standards and best practices
• Strong expertise in ML, GenAI and agentic AI, with knowledge of lifecycle frameworks and governance practices
• Provide hands-on design, validation, and testing contributions in pipelines and prototypes

• 4–7+ years of experience in AI/ML validation, model risk, or AI governance in regulated environments
• Advanced Python programming skills with experience in pandas, scikit-learn, LightGBM
• Ability to develop clean, modular, maintainable code with emphasis on reproducibility and quality
• Autonomy and proactivity with regulatory awareness (EU AI Act), explainability tools, and modern AI architectures
• Italian and English working proficiency
• Analytical thinking, risk mindset, strong communication, ability to challenge assumptions, strong documentation
• Ability to work independently and in a team with diverse mindsets
• Multitasking and deadline management
• Willingness to learn and tackle complex topics

• analytical thinking
• risk mindset
• clear communication
• advanced Python (OO design)
• pandas
• scikit-learn