Legal & Compliance Tech IT Product Manager

AI-First Product Ownership & Roadmap (Legal & Compliance Technology)

• Own the product vision, AI roadmap, and backlog for the legal and compliance technology portfolio within EAIT, with AI and automation as the default lens for every initiative.
• Set a multi-year vision for an AI-augmented legal function, identifying where generative AI, AI agents, and automation can eliminate manual effort, accelerate cycle times, and improve quality and risk outcomes.
• Align roadmap priorities with Legal & Compliance leadership, EAIT’s AI transformation strategy, and enterprise architecture standards.
• Define success metrics and outcomes—including AI adoption, automation rate, accuracy, cycle-time reduction, and cost-to-serve—to measure business value and system effectiveness.

AI, Automation & Agentic Workflows

• Design and deliver generative-AI capabilities across the legal stack: AI-assisted contract drafting, review, redlining, clause extraction, and risk flagging; AI summarization of matters, contracts, and legal documents; and natural-language search across legal knowledge.
• Build and productize AI agents that execute or augment core legal and compliance processes—such as legal intake triage and routing, NDA and standard-contract self-service, obligation and renewal tracking, policy Q&A, and regulatory-change monitoring.
• Define and prioritize Model Context Protocols (MCPs) and integrations that securely connect legal systems (CLM, matter management, document management, GRC) to large language models and orchestration frameworks.
• Apply retrieval-augmented generation (RAG) over contracts, policies, and legal knowledge bases to deliver grounded, citable answers for legal and business stakeholders.
• Evaluate, pilot, and scale AI legal-tech vendors and native AI features (e.g., contract AI, AI assistants, e-discovery AI), running structured proofs-of-concept and build-vs-buy assessments.
• Establish evaluation and quality processes for AI features—prompt design, model selection and tradeoffs, accuracy and hallucination testing, human-in-the-loop review, and continuous tuning.

Business Process & Solution Design

• Lead end-to-end, AI-augmented redesign of core legal workflows—contract lifecycle management, matter intake and management, outside-counsel and legal-spend (e-billing), e-signature, entity and corporate records management, and legal hold and e-discovery.
• Translate business requirements into clear functional specifications and solution designs—including where AI augments, automates, or fully owns a step, and where humans stay in the loop—for EAIT delivery teams.
• Ensure solutions are scalable, auditable, and aligned with data privacy, security, internal controls, and compliance standards, including protection of privileged and sensitive information in all AI workflows.

Enterprise Applications Enablement

• Partner with EAIT engineers, administrators, AI architects, and platform owners to design and deliver enhancements, integrations, MCPs, and AI agents across legal technology platforms.
• Review and approve configurations, workflows, integrations, prompts, and agent designs to ensure they meet business, legal, and IT governance requirements.
• Guide prioritization of enhancements, AI capabilities, upgrades, and technical-debt remediation across legal-managed platforms.

Stakeholder Partnership & Delivery

• Serve as the primary EAIT point of contact for Legal & Compliance stakeholders and as a champion for AI-first ways of working across the legal function.
• Manage intake, prioritization, and delivery of requests, balancing stakeholder needs with EAIT capacity and the AI roadmap.
• Lead cross-functional initiatives from discovery through deployment, ensuring clear communication, change management, and timely execution.

Responsible AI, Controls, Privacy & Insights

• Govern the full lifecycle of AI agents and MCPs in the legal domain, ensuring responsible-AI practices: guardrails, privilege protection, data governance, access controls, auditability, and human oversight.
• Partner with Legal, IT risk, Security, and audit teams to ensure AI-enabled systems and processes support privacy, regulatory, and SOX-related requirements and safeguard attorney-client privilege and sensitive data.
• Define and oversee KPIs and operational metrics for legal and compliance systems, including AI accuracy, reliability, adoption, and ROI.
• Collaborate with data, BI, and AI teams to deliver dashboards, analytics, and AI-driven insights that support data-driven legal operations.

Change Management, AI Enablement & Adoption

• Drive successful adoption of AI tools and transformed processes across the Legal & Compliance organization through training, communication, and change management.
• Act as an AI fluency champion, helping legal and compliance professionals integrate generative AI and agents into daily workflows.

Requirements

• 5+ years of product management experience, ideally in legal tech, enterprise applications, or AI-enabled SaaS products.
• Strong AI literacy with hands-on experience designing or shipping generative AI features, AI agents, RAG systems, or agentic workflows.
• Deep knowledge of legal and compliance technology stack (CLM, matter management, e-billing, GRC, e-signature, e-discovery).
• Proven ability to translate complex business and legal requirements into technical specifications and roadmaps.
• Experience with enterprise systems implementation, integrations, and platform ownership.
• Strong stakeholder management and cross-functional leadership skills, especially partnering with legal, compliance, security, and engineering teams.
• Understanding of data privacy, security, compliance (including SOX), and attorney-client privilege considerations in AI systems.
• Bachelor's degree in a relevant field (Computer Science, Law, Business, or equivalent experience).

Nice-to-Haves

• Experience in a high-growth tech company or scaling legal operations.
• Familiarity with Model Context Protocols (MCPs), orchestration frameworks, or building AI agents.
• Background in legal (JD or paralegal experience) or prior work in Legal Operations (LegalOps).
• Experience with specific platforms like LinkSquares, SirionLabs, Thomson Reuters, or ServiceNow GRC.
• Track record of measuring and reporting on AI ROI and operational metrics.