Director, Data Science & AI Engineering

About this role

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 governance, controls, traceability, and human oversight. • Direct model development, fine-tuning, evaluation, and optimization initiatives utilizing proprietary firm data while ensuring compliance with confidentiality, privilege, intellectual property, and security requirements. • Lead the firm’s analytics and reporting initiatives, including data modeling, warehouse/lakehouse strategy, and the development of dashboards and business intelligence tools that provide actionable operational, financial, staffing, and AI utilization insights to firm leadership.

MLOps, Engineering Excellence, and Governance • Establish and oversee core AI engineering and operational standards, including source control, CI/CD processes, infrastructure-as-code, observability, environment management, evaluation frameworks, and production support practices. • Lead and maintain scalable MLOps/LLMOps capabilities, including prompt and model versioning, automated testing, performance monitoring, drift detection, latency and cost tracking, and incident management processes. • Partner with Information Security, IT, Privacy, Risk, and the Office of General Counsel to ensure AI solutions comply with firm standards related to confidentiality, privilege, client obligations, data governance, and regulatory requirements. • Support the development and execution of the firm’s AI governance framework, including acceptable use standards, vendor and model evaluation processes, testing protocols, and risk management practices. • Evaluate and recommend build-versus-buy strategies for AI and technology solutions, leveraging commercial platforms where appropriate and developing custom solutions where the firm can achieve strategic or operational advantage.

Collaboration Across the Firm • Collaborate closely with Knowledge Management & Innovation leadership to align AI development initiatives with practice group priorities, business needs, and user adoption strategies. • Partner with attorneys, practice groups, and business stakeholders throughout the solution development lifecycle to ensure AI tools and workflows address operational and client service needs effectively. • Communicate technical concepts, architectural decisions, and implementation trade-offs clearly and effectively to business and legal stakeholders. • Represent the firm in interactions with vendors, clients, industry groups, peer organizations, and the broader legal AI community to support innovation, strategic partnerships, and talent development.

REQUIRED EDUCATION, KNOWLEDGE & EXPERIENCE • Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Data Science, or a related quantitative field, or equivalent combination of education and relevant professional experience. Advanced degrees preferred. • 10+ years of progressive experience in data science, machine learning, AI engineering, or a related technical discipline, including demonstrated leadership experience building and manag

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