The LINCS organization manages security and compliance across Meta's owned and leased data centers, facilities and operational technology, labs, supply chain and logistics, terrestrial networks, and subsea cable systems. We are looking for a manager to lead the Security and Compliance team. You will lead engineers and specialists, set strategy, and manage a portfolio spanning Meta's infrastructure.

Qualifications:

Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience 10+ years of experience in infrastructure security, network security, enterprise compliance, or telecommunications security 5+ years of experience managing technical teams, including senior individual contributors and technical leads Experience owning a security or compliance program end-to-end in a large-scale network, data center, or critical infrastructure environment Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience managing blended teams of employees, contingent workers, and managed service providers Experience securing subsea, facilities, industrial control and operational technology, or other regulated critical infrastructure environments Experience leading a technical team through reorganization or rapid scope change Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience managing audit, regulatory, control, and remediation programs, including direct engagement with external auditors or regulators Experience applying automation, AI, or data products to scale security or compliance operations Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)