Lead AI Validation

Questa posizione è in Generali Italia

Riassunto dell'opportunità da parte della Joinrs AI:
Generali Italia cerca un Lead AI Validation & Governance (GenAI & ML) con laurea in discipline STEM o esperienza equivalente per guidare la validazione e la governance di sistemi AI avanzati. Il ruolo prevede responsabilità strategiche e operative nell'assicurare l'affidabilità, la conformità e l'efficacia dei modelli AI in contesti aziendali critici. Offerta include contratto di livello VI CCNL ANIA, RAL tra 43K€ e 55K€, smart working, welfare aziendale e programmi di formazione e sviluppo continuativi.

Il processo di selezione sarà interamente gestito da Generali Italia.

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Within the Group Data, Artificial Intelligence and Automation department, we are looking for a highly experienced Data Scientist / Data Engineer to lead AI Validation and Governance across both traditional Machine Learning and next-generation Generative and Agentic AI systems.

The Lead AI Validation & Governance (GenAI & ML) will play a pivotal role in defining, implementing, and scaling the Group's AI governance and model risk framework, ensuring that AI systems are robust, explainable, compliant, and fit for purpose in business-critical contexts.

This role sits at the intersection of AI model validation, model risk management, and Responsible AI, providing independent oversight and technical leadership across the entire AI lifecycle — from design and development to deployment, monitoring, and periodic review.

In addition to its strategic and governance responsibilities, this role is expected to remain strongly hands-on, actively contributing to the design, validation, and testing of AI models and systems.

The ideal candidate combines deep technical expertise with a pragmatic mindset, and is comfortable developing and reviewing model validation code; working directly with ML and GenAI pipelines; building prototypes, validation tools, and monitoring solutions; interacting with data, models, and APIs in a production-oriented environment.

Key responsibilities of the role will include:

• Perform independent validation and challenge of AI/ML and agentic/Generative AI systems across the full lifecycle, including model design, data quality, and performance (accuracy, robustness, explainability, fairness)
• Align validation and governance practices with applicable regulations (e.g., EU AI Act), internal guidelines, and risk appetite, translating requirements into operational processes and controls
• Identify and assess key risks (bias, explainability, compliance), and define appropriate validation controls and mitigation actions
• Define and implement continuous monitoring and alerting mechanisms for AI systems in production (e.g., data/performance drift, emerging risks such as GenAI hallucinations)
• Ensure ongoing compliance through lifecycle oversight, including periodic re-validation of models
• Design and implement reusable functionalities to enable scalable governance and monitoring of AI models and agents
• Collaborate with data scientists, engineers, and cross-functional stakeholders, acting as a second line of defense to challenge assumptions and strengthen decision-making
• Maintain robust documentation and support audit and regulatory reviews, while contributing to standards, templates, and best practices

Requirements:

• Strong expertise in machine learning, Generative AI and agentic AI, with solid knowledge of AI lifecycle frameworks and validation/governance practices
• 4–7+ years of experience in AI/ML validation, model risk, or AI governance preferably within structured or regulated environments
• Advanced Python programming skills (object-oriented design) with hands-on experience in core data science libraries (e.g., pandas, scikit-learn, LightGBM)
• Proven ability to develop clean, modular, maintainable code, with strong focus on robustness, reproducibility, and quality
• High autonomy and proactivity, with strong collaboration skills and good understanding of regulatory frameworks (e.g., EU AI Act), explainability tools, and modern AI architectures
• Italian and English working proficiency

Soft skills include:

• Analytical thinking, risk mindset, communication skills, ability to challenge assumptions, strong documentation discipline
• Ability to work independently and as part of a team, collaborating with individuals with diverse mindsets