Job Description

The core purpose of this role is to lead the implementation, integration, and adoption of AI agents to handle commercial contracts processes, including intake, drafting, compliance checks, and playbook-driven negotiation. Their primary mandate is to deliver demonstrated efficiency gains across commercial areas, with a Year 1 target of 20-30% efficiency gains in contracts AI

This position supports the global operation of Meta by ensuring that its critical commercial agreements are executed and managed with speed, precision, and risk awareness. The role’s fit is characterized by:

Enabling Global Operations: The AI contracts system is relied upon by lawyers, clients, and the broader employee base to execute and manage all global commercial contracts.

Driving Efficiency and Scalability: The work is designed for durable, expanding scope. After anchoring the work in commercial contracts, the role will build reusable frameworks to transfer AI patterns to adjacent legal domains.

Influencing Technology Strategy: The role influences Meta Legal’s broader AI strategy and operating model through demonstrated results, ultimately leading to a Legal AI interoperability platform by Year 3.

Responsibilities
Accelerate AI Adoption: Drive adoption across all commercial verticals, identifying work that can be transformed with existing solutions or designing new builds to fill current gaps
* Ensure Legal Integrity & Compliance: Configure playbooks, integrate our central solutions (Ivo/Contracts Hub), and translate internal (Meta policies, risk postures) and external requirements (e.g., FTC Order, GDPR, SOX) into AI guardrails, ensuring all AI outputs are legally sound, compliant, and auditable
* Strategic Expansion: While initially focused on commercial contracts to deliver efficiency gains, the role is structured for durability, potentially providing critical partnership on broader AI frameworks across adjacent legal domains (i.e., Corporate Legal, Compliance, eDiscovery, IP)
* Owning the technical strategy and build path for a highly customized system that weaves third-party AI solutions into Meta’s homegrown Contracts intelligence platform
* Designing AI guardrails and controls to ensure the systems are compliant, low-risk, and auditable, staying ahead of global AI regulatory landscapes (e.g., EU AI Act, U.S. state-level laws)

Qualifications
10+ years experience with commercial contracts (such as sales-side, buy-side, JVOs, Partnerships deals, and experience with re-papering and contract uplift)
* 3+ years experience with legal tech implementation: Led enterprise legal technology solutions, CLM or contract automation and intelligence. Experience integrating third-party point solutions into homegrown systems via API/MCP required
* AI in Legal: hands-on experience with GenAI and AI models/tools
* Demonstrated experience solving problems at the platform level: Builds reusable frameworks, not bespoke one-offs. Thinks about how patterns transfer across legal domains
* Governance & Risk Fluency: Practical experience with privacy, AI governance, and commercial risk controls. You design for compliance, not just efficiency
* Global AI Regulatory Awareness: Working knowledge of the EU AI Act, emerging U.S. state AI laws, and AI-related contractual obligations (model training restrictions, transparency clauses, data processing terms)
* Vendor & Platform Management: Experience managing enterprise legal tech or AI vendors, including Service Level Agreement negotiation, performance management, and contingency planning
* Cross-functional: Experience working cross-company departments, particularly defining Engineer-ready specs. Credibility with executive Legal leadership (GCs, CLOs) and Engineering leadership
* Change leadership: Experience scaling legal tech orgs with measurable outcomes Adjacent legal domain fluency (privacy, IP, employment, litigation ops) is a consideration, but should not substitute for contracts depth
* Experience with hands-on configuring GenAI for contract review, drafting, and negotiation. Prompt engineering, evals, and model risk review
* Prior exposure to adjacent legal domains (eDiscovery, product counsel, employment, IP, regulatory) is valuable for platform consistency, ramp-up, and scale-out
* Experience with enterprise legal AI platforms (e.g., Harvey, Ironclad, IVO, Legora, or similar), MCP / agent orchestration, Lean / Six Sigma, high-growth tech environments
* Juris Doctor (JD) degree
* Experience with commercial contracts: NDAs, DPAs, MSAs, PSAs, IP, SaaS, privacy terms, etc