Director of Artificial Intelligence

Finnegan•Washington, DC

21h•Hybrid

About The Position

The Director of AI leads the firm’s enterprise-wide artificial intelligence strategy and advances legal and operational excellence through responsible, impactful AI adoption. This role guides the transition from isolated experimentation to a cohesive, governed AI program that positions AI as a core business enablement function. Reporting to the Director, Litigation Technology and Knowledge Management, the Director of AI defines and executes a comprehensive AI roadmap, translating technical concepts into measurable business value across legal and operational workflows. The role oversees the development, deployment, and optimization of AI and machine learning solutions, with a focus on cost efficiency, scalability, ethical use, and sustained impact. The Director serves as a trusted advisor and thought partner to firm leadership, working cross functionally with senior stakeholders to drive adoption, establish governance, and fosters a culture of innovation.

Requirements

Master’s degree or PhD in Computer Science, AI, Data Science, or a related quantitative field required; Juris Doctor (J.D.) or advanced AI/legal technology preferred
7+ years leading AI, machine learning, or legal technology initiatives, including people and program leadership, preferably in a law firm or professional services environment.
Proven delivery of AI solutions for legal use cases (e.g., research, contract analysis, eDiscovery, due diligence).
Significant experience in a large law firm (AmLaw 100/200) or comparable legal setting, with familiarity in legal operations, knowledge management, or practice support.
Demonstrated success partnering with attorneys to implement AI that measurably improves efficiency, cost, throughput, or revenue, supported by defined KPIs and quantifiable results.
Experience building AI capabilities from the ground up in complex or regulated environments, including vendor management, build vs buy decisions, and change management.
Strong command of AI/ML concepts and applications, including LLMs, generative AI, NLP, predictive analytics, agentic systems, and vector-based search.
Working knowledge of Model Context Protocol (MCP), agent orchestration frameworks, tool‑use patterns, and reusable AI skill/prompt libraries, with the judgment to govern their use in a confidential, ethics‑regulated legal environment.
AI/ML literacy across modern languages, frameworks, cloud platforms, and data engineering stacks (hands on coding not required).
Familiarity with leading legal AI platforms (e.g., Claude, Legora,LexisNexis, Westlaw, Harvey, CoCounsel, ChatGPT).
Solid understanding of data governance, information lifecycle management, and data quality standards.
Exceptional leadership and communication skills, with the ability to influence attorneys, technologists, and senior leadership.
Strategic, pragmatic, and data-driven decision-maker with strong change management instincts.
Strong business-outcome mindset
Ability to translate AI investments into clear business value through performance frameworks, ROI modeling, and executive level storytelling.
Trusted advisor to partners, valued for sound judgment, ethical awareness (AI ethics, privacy, legal standards), and a calm, impact focused approach that embeds AI seamlessly into legal workflows.

Nice To Haves

Knowledge of intellectual property litigation or prosecution workflows and AI applications in those areas.
Experience in healthcare, finance, or IP-focused environments.
Background in document automation, generative AI platforms, data strategy, information governance, or firmwide cost reduction initiatives.

Responsibilities

Defines and executes a firm-wide AI vision and roadmap aligned with strategic objectives.
Champions AI adoption across practice areas (including IP litigation, prosecution, and transactional work) and prioritizes high-impact use cases that drive efficiency, quality, and client value.
Leads the firm’s evolution from pilots to scalable, production-ready AI solutions through disciplined prioritization and visible business wins.
Evaluates and implements emerging AI technologies (e.g., LLMs, generative AI, NLP, agentic systems, Model Context Protocol (MCP) connectors, and AI orchestration frameworks) and designs secure, scalable, and governable architectures to support legal use cases such as legal research, prior art analysis, eDiscovery, and workflow automation.
Provides technical leadership across the AI lifecycle, from ideation and model development through deployment, MLOps, and monitoring, including agent evaluation, tool integration via MCP, and lifecycle management of reusable AI skills and prompt libraries.
Oversees end-to-end delivery of AI initiatives, ensuring quality, timeline, and scope expectations are met.
Establishes best practices for development, testing, deployment, and performance monitoring.
Defines and tracks KPIs to measure adoption, efficiency gains, cost reduction, and ROI, enabling data-driven decisions about technology investments.
Partners closely with attorneys, IT, knowledge management, and business teams to design and deploy AI solutions that integrate seamlessly into existing workflows.
Leads training, communication, and change management efforts to drive sustained adoption, identify internal champions, and ensure tools deliver real-world impact.
Defines and implements governance frameworks for ethical, compliant, and secure AI use, addressing legal ethics, data privacy, and law-firm-specific confidentiality requirements such as client data segregation and privilege protection.
Collaborates with IT and knowledge management leadership to strengthen data quality, information governance, and foundational data infrastructure required for reliable AI deployment.
Evaluates, selects, and manages AI vendors and strategic partners, including build-versus-buy decisions, contract negotiations, and integrations.
Manages budgets for AI initiatives, optimizing resource allocation to maximize ROI and align with firm priorities.
Builds, mentors, and leads a cross-functional AI team, fostering a culture of innovation, collaboration, and continuous learning.
Scales the team over time as the firm’s AI capabilities mature.
Leads the design and governance of agentic AI capabilities, including multi‑step agent workflows, Model Context Protocol (MCP) integrations with firm systems (DMS, time and billing, conflicts, KM, and matter data), and orchestration of multiple models, tools, and data sources behind a unified attorney experience.
Builds and curates a firmwide library of reusable AI “skills,” prompt templates, and agent patterns that codify Finnegan’s legal expertise and accelerate adoption across practice groups, with version control, evaluation, and guardrails appropriate for IP litigation, prosecution, and transactional work.
Models and personally demonstrates AI‑driven productivity by using firm‑approved AI tooling and agentic workflows in the day‑to‑day execution of the role, including research, analysis, drafting, vendor evaluation, and program reporting.
Establishes productivity benchmarks and dashboards that quantify time saved, throughput, quality improvements, and realization impact attributable to AI, and publish recurring “AI productivity” updates to firm leadership that translate adoption metrics into strategic outcomes and future‑state capability planning.