Reality Labs Revenue Operations Lead

The Reality Labs ('RL') Revenue Operations Lead leads the end-to-end Order to Cash (OTC) function for Meta's Reality Labs hardware business, responsible for collecting ~$2B in cash annually, managing extended credit risk, and enabling scalable revenue growth across global markets. This role serves as the strategic leader accountable for credit, billing, collections, claims/deduction management, and cash application for all RL B2B customers.

Operating at the intersection of finance, operations, and technology, this leader drives the vision and execution of AI-powered automation, process excellence, and cross-functional partnership to ensure RL Revenue Operations delivers consistent, measurable results while scaling to support new products, markets, localizations and go-to-market programs.

Responsibilities

• Define and execute the RL Revenue Operations strategy
• Drive the operational roadmap to maximize automation, minimize manual effort, and scale processes for business growth
• Partner with senior leadership across Sales, Legal, Channel Operations, Channel Marketing, Accounting, and Tax to align on revenue growth priorities and remove operational blockers
• Lead new market entry, product launches, and go-to-market initiatives from a revenue operations perspective, ensuring credit, claims and collections infrastructure is ready at launch
• Own and govern the end-to-end OTC process for RL
• Drive process excellence through process, controls, and continuous improvement initiatives through AI
• Lead change management for system migrations, process redesigns, and new capability rollouts — ensuring adoption and compliance across teams
• Lead, develop, and mentor the RL team and oversee BPO partner performance

Minimum qualifications

• Bachelor's degree in Business, Finance, or a related field
• 7+ years of progressive experience in financial operations, revenue operations, or order-to-cash management
• Deep expertise in credit, collections and claims/deduction management processes
• Ability to develop and execute operational strategy in a fast-paced, high-growth environment
• Strong cross-functional leadership and stakeholder management skills at senior levels
• Experience driving process automation and technology adoption in financial operations
• Experience communicating operational strategy and performance outcomes to executive stakeholders through presentations, reports, and cross-functional forums Experience managing multi-national operations across 3+ regions with varying regulatory requirements
• Experience managing BPO relationships and driving third-party operational performance
• Experience in hardware, consumer electronics, or retail channel revenue operations
• Ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Track record of scaling operations from early-stage to mature, high-volume execution
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

Preferred qualifications

• Experience managing multi-national operations across 3+ regions with varying regulatory requirements
• Experience managing BPO relationships and driving third-party operational performance
• Experience in hardware, consumer electronics, or retail channel revenue operations
• Ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Track record of scaling operations from early-stage to mature, high-volume execution
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)