Director, Data Science & AI Engineering

The Director Data Science & AI Engineering will lead the development and execution of the Firms 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 Firms 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 firms 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 firms 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 firms 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 firms 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

• Bachelors 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 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.

PREFERRED SKILLS & QUALIFICATIONS

• 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.

PHYSICAL REQUIREMENTS

• Ability to sit and stand for extended periods.
• Ability to lift up to 15 pounds.

Qualified applicants with arrest and conviction records will be considered for the position in accordance with the California Fair Chance Act.

The expected salary range for this position is $290000 - $440000. Final compensation will be determined based on several factors including but not limited to relevant experience qualifications skill set and geographic location.

Pillsbury Winthrop Shaw Pittman LLP is an Equal Opportunity Employer.

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