Director, Data Science & AI Engineering

Nashville, Tennessee Job Description The Director, Data Science & AI Engineering will lead the development and execution of the Firm’s enterprise data science, analytics, and AI engineering strategy. This role is responsible for building and managing a multidisciplinary team of Data Scientists, Data Analysts, and MLOps / AI Engineers focused on delivering innovative, production-ready AI solutions that support the Firm’s legal and business operations. Key responsibilities include overseeing the design, implementation, and optimization of LLM-powered applications, retrieval-augmented generation (RAG) systems, AI agents, custom models, advanced analytics, and business intelligence platforms that provide actionable matter, financial, and operational insights to firm leadership. This position serves as a strategic and hands-on leadership role within a rapidly evolving AI environment, responsible for establishing scalable architecture, governance, evaluation standards, security practices, and operational frameworks appropriate for a highly regulated professional services organization. The Director will work closely with the Knowledge Management & Innovation function and other firm stakeholders to translate legal and operational needs into practical AI-driven solutions that enhance efficiency, decision-making, and service delivery across the KEY RESPONSIBILITIES Leadership Design and implement the operational framework, team structure, delivery processes, and performance metrics for the firm’s Data Science & AI Engineering function. Recruit, develop, and lead a high-performing multidisciplinary team of Data Scientists, Data Analysts, and MLOps/AI Engineers, establishing strong technical and cultural standards. Oversee day-to-day team operations, including strategic planning, prioritization, project delivery, performance management, mentorship, and employee development. Foster a collaborative, innovative, and business-focused culture centered on delivering practical AI and analytics solutions that support legal and operational outcomes. Build & Lead Internal AI Platforms and Solutions Design, develop, and deploy internal AI applications leveraging firm-approved large language models (LLMs), with a focus on scalability, evaluation, observability, and cost efficiency. Lead the development and management of the firm’s retrieval-augmented generation (RAG) capabilities, including ingestion pipelines, embeddings, vector and hybrid search, re-ranking, and citation-supported response generation across firm knowledge and matter data. Oversee integrations between AI applications and internal business systems, including document management, matter management, financial, timekeeping, and knowledge management platforms, utilizing secure and governed integration frameworks such as Model Context Protocol (MCP). Develop and operationalize AI-driven workflows and agent-based solutions that support legal and business processes, incorporating appropriate go