Senior Consultant – AI Transformation & Decisioning (Legal Environment)

The project supports complex data, process, and AI transformation programmes within legal or regulatory environments, such as the EFSA context. It involves designing and delivering AI-enabled solutions that enhance decision-making, automate processes, and improve efficiency while ensuring compliance with legal, regulatory, and governance frameworks.

• Experience in AI-enabled transformation programmes including GenAI and Machine Learning
• Experience working in or with legal, regulatory, or compliance-driven environments
• Experience redesigning end-to-end business processes leveraging AI
• Ability to elicit and document AI-related requirements and use cases
• Experience delivering AI components into production environments
• Experience integrating AI services within enterprise ecosystems such as Azure-hosted AI, data platforms, and vector search
• Ability to conduct data analysis with strong attention to data quality and governance
• Ability to model complex decision processes combining human and AI inputs
• Solid understanding of AI/ML concepts and decision intelligence frameworks
• Ability to align AI solutions with legal and regulatory requirements
• Strong expertise in process optimisation and intelligent automation
• Proven ability to translate business and legal needs into technical solutions
• Excellent stakeholder management in complex, multi-stakeholder environments
• Strong analytical and problem-solving mindset

Nice to have:

• Experience using AI tools in day-to-day workflow
• Experience with data platforms such as Azure Data Lake, Synapse, Databricks
• Knowledge of Python or SQL

• Drive AI-enabled transformation initiatives in complex, regulated environments
• Elicit, analyse, and document AI use cases, requirements, and business needs including legal and compliance aspects
• Lead end-to-end process redesign with integrated AI capabilities
• Design and support implementation of decision intelligence models combining human judgment and AI outputs
• Contribute to delivery and deployment of AI components into production environments
• Ensure integration of AI services within enterprise architectures (Azure AI, data platforms, vector search)
• Perform data-driven analysis focusing on data quality, traceability, and compliance
• Collaborate with multi-disciplinary stakeholders including legal, business, IT, data, and external providers
• Ensure compliance with governance, security, legal, and enterprise architecture standards
• Support business analysis activities within broader transformation initiatives