Legal & Compliance Tech IT Product Manager

Gusto, Inc.•San Francisco, CA

10h•$221,000 - $247,000•Hybrid

About The Position

As a key member of Enterprise Applications IT (EAIT), the Legal Tech IT Product Manager owns the AI-first strategy, roadmap, and delivery of the enterprise applications supporting Gusto’s Legal & Compliance organization. This is an AI-forward product role: you will reimagine how legal and compliance work gets done by embedding generative AI, AI agents, and intelligent automation into systems like contract lifecycle management (CLM), matter and legal-spend management, e-signature, entity and corporate records management, legal hold and e-discovery, and governance, risk, and compliance (GRC) platforms. Acting as the primary interface between Legal & Compliance teams and EAIT delivery resources, you will translate business needs into well-defined, AI-enabled product requirements, guide solution design, and drive continuous improvement across core legal and compliance processes. In line with Gusto’s enterprise systems strategy, you will help shift legal operations from reactive, manual workflows to predictive, context-aware, and self-improving platforms—designing agentic workflows and Model Context Protocols (MCPs) that connect legal systems to large language models—while ensuring privilege protection, security, compliance, and measurable impact. This role blends product leadership and deep systems knowledge with strong AI literacy and a bias toward applying AI to every part of the legal technology stack.

Requirements

Bachelor’s degree in Information Systems, Business Administration, Legal Studies, or a related field.
8+ years of experience in enterprise applications, legal operations / legal technology, business systems, or product management, with hands-on expertise supporting legal and/or compliance functions.
Demonstrated experience delivering AI-powered products or features—generative AI / large language models, AI assistants, or intelligent automation—ideally within legal, compliance, or enterprise applications, with a clear bias toward applying AI to solve business problems.
Working knowledge of leading LLM platforms (e.g., OpenAI, Anthropic, Gemini) and core GenAI techniques such as prompt engineering, retrieval-augmented generation (RAG), evaluation, and guardrails, with the ability to reason about model tradeoffs.
Familiarity with AI agent and orchestration frameworks (e.g., LangChain, CrewAI, Semantic Kernel) and Model Context Protocols (MCPs), and experience integrating AI with enterprise systems is a strong plus.
Hands-on experience with legal technology platforms such as contract lifecycle management (e.g., Ironclad, Agiloft, DocuSign CLM), matter management and e-billing (e.g., SimpleLegal, Brightflag, Legal Tracker), e-signature (e.g., DocuSign), entity management, legal hold / e-discovery, and/or GRC tools—including their native AI capabilities.
Experience evaluating, selecting, and deploying AI legal-tech vendors and running proofs-of-concept and build-vs-buy assessments.
Strong commitment to responsible, secure, and explainable AI, with experience embedding privacy, privilege protection, audit controls, and SOX-aligned governance into AI-enabled workflows.
Experience owning or managing enterprise application products within an IT or EAIT-style organization, and the ability to translate business needs into product roadmaps, functional requirements, and delivered solutions.
Strong stakeholder management skills and the ability to partner effectively across Legal, Compliance, IT, and executive leadership, with excellent written and verbal communication and the ability to influence without authority.
Growth mindset and the ability to operate in ambiguity, define standards where none exist, and scale AI solutions from proof-of-concept to enterprise-wide adoption.

Nice To Haves

Relevant certifications (PMP, product management, AI/ML, or legal operations / CLM certifications) are a plus.

Responsibilities

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.
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.
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.
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.
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.
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.
Drive successful adoption of new AI capabilities through training, documentation, prompt and playbook libraries, and hands-on change management.
Coach legal and compliance teams on safe, effective, and confident use of AI tools, and act as the subject-matter expert for legal AI and technology within EAIT, promoting best practices and standardization.