As a key player in our data team, you will design and develop the backbone infrastructure that powers our Legal AI agents. You’ll be responsible for transforming hundreds of thousands of historical legal cases into clean, high-quality training data — the foundation for building powerful and scalable AI models.

• Expand and optimize our Databricks/Delta Lakehouse environment on AWS, crafting GDPR-compliant data models, data contracts, and clear data lineage
• Build and maintain robust ELT pipelines using PySpark, dbt, and Airflow, including automated quality checks, dataset versioning, and comprehensive testing
• Lead the design and management of a scalable annotation process, including tooling, guidelines, and quality assurance for a team of 20 paralegals
• Develop transparent, data-driven dashboards (e.g., Tableau) to detect bias, data gaps, and model risks — providing actionable insights to executives and specialist teams
• Define gold standards, adversarial test sets, and evaluation metrics for faithfulness, citation accuracy, and model alignment to ensure rigorous AI agent validation
• Own the Reinforcement Learning from Human Feedback (RLHF) data cycle: curate human feedback datasets, train reward models, and monitor alignment metrics
• Lead, mentor, and grow the data team while collaborating closely with AI engineers on RAG workflows and LLM evaluation