Director, Data Science & AI Engineering

Pillsbury Winthrop Shaw Pittman • Nashville, DC

21h • Onsite

About The Position

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 firm.

Requirements

• 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.
• 10+ years of progressive experience in data science, machine learning, AI engineering, or a related technical discipline, including demonstrated leadership experience building and managing high-performing technical teams.
• Proven success designing, deploying, and supporting production AI/ML solutions, including large language model (LLM) applications, retrieval-augmented generation (RAG) systems, and agent-based workflows.
• Strong technical foundation with the ability to evaluate system architecture, engineering approaches, model performance, and technical design decisions across AI and analytics platforms.
• Deep understanding of modern AI technologies and architectures, including foundation models, embeddings, vector databases, hybrid search, RAG methodologies, agent frameworks, Model Context Protocol (MCP), prompt engineering, model evaluation, fine-tuning, and operational scalability considerations.
• Experience establishing and supporting MLOps/LLMOps practices, including cloud infrastructure, deployment automation, monitoring, security, and operational governance.
• Demonstrated experience leading enterprise analytics and business intelligence initiatives, including the development of executive-facing dashboards and reporting solutions that support strategic decision-making.
• Strong leadership, organizational, and problem-solving skills, with the ability to operate effectively in fast-paced, evolving, and highly collaborative environments.
• Excellent written and verbal communication skills, including the ability to communicate complex technical concepts, AI risks, and architectural decisions clearly to executive leadership, attorneys, and non-technical stakeholders.
• Sound judgment regarding AI governance, privacy, security, confidentiality, and ethical considerations associated with deploying AI technologies in regulated and data-sensitive environments.

Nice To Haves

• Advanced degrees preferred.
• Experience within the legal, professional services, financial services, or another highly regulated, document-intensive industry environment.
• Legal education or prior legal industry experience is a plus.
• Familiarity with legal technology and enterprise data platforms, including document management systems, matter and timekeeping systems, knowledge management platforms, eDiscovery technologies, and litigation support tools.
• Hands-on experience with AI platforms and tooling from providers such as OpenAI, Anthropic, Google, Microsoft, and open-source AI ecosystems, including familiarity with legal-specific AI platforms such as Harvey, CoCounsel, and Legora.
• Active participation in the AI engineering, machine learning, or applied research community through publications, speaking engagements, open-source contributions, or established industry networks.

Responsibilities

• 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.
• 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.
• 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.
• 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.

Benefits

• The expected salary range for this position is $290,000 - $440,000 . Final compensation will be determined based on several factors, including but not limited to, relevant experience, qualifications, skill set, and geographic location.

What This Job Offers

• Job Type: Full-time
• Career Level: Director