Security Engineering Manager, Anti-Scraping

Meta•Menlo Park, CA

10d•$184,000 - $257,000

About The Position

Meta is seeking a Security Engineering Manager to lead the Anti-Scraping engineering team within the Privacy Engineering organization. The team builds detection systems, enforcement pipelines, and adversarial defenses to protect user privacy, platform integrity, and data security across Meta’s family of apps from unauthorized data collection. The role leads engineers developing scalable anti-scraping infrastructure at the intersection of privacy engineering, threat detection, and abuse prevention. It partners with Privacy, Security, Legal, Policy, and Product teams to define strategy, drive technical roadmaps, and deliver systems that proactively identify and mitigate scraping threats at scale.

Requirements

8+ years of experience in security engineering, privacy engineering, abuse prevention, or a closely related technical domain.
4+ years of experience managing software or security engineering teams, including performance management and hiring.
Experience designing or operating systems for threat detection, bot mitigation, rate limiting, or abuse prevention at scale.
Experience building cross-functional relationships and influencing technical and non-technical stakeholders on security or privacy strategy.
Experience communicating technical risk assessments and enforcement tradeoffs in written form to leadership and partner teams.
BS in Computer Science or equivalent experience in Security.

Nice To Haves

Demonstrated ability to integrate AI tools to optimize detection workflows and drive measurable improvements in coverage or enforcement efficiency.
Demonstrated ability to integrate AI tools to optimize or redesign workflows and drive measurable impact, such as efficiency gains or quality improvements.
Experience applying machine learning or behavioral analytics to abuse detection or anomaly identification in large-scale production environments.
Experience adhering to and implementing responsible, ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews.
Demonstrated ongoing AI skill development, such as prompt/context engineering and agent orchestration, and staying current with emerging AI technologies.
Experience working within a privacy or regulatory compliance context, including familiarity with data protection frameworks relevant to unauthorized data collection.
Experience with adversarial systems, including knowledge of scraping techniques, bot infrastructure, and evasion methods used by threat actors.

Responsibilities

Lead and develop a team of engineers building detection, enforcement, and mitigation systems to combat unauthorized data scraping across Meta's platforms.
Define and drive the technical roadmap for anti-scraping infrastructure, balancing near-term threat response with long-term platform resilience.
Partner with Privacy, Security, Legal, and Policy teams to align anti-scraping strategy with regulatory obligations and user privacy commitments.
Oversee the design and operation of adversarial detection pipelines that identify scraping patterns across web, mobile, and API surfaces.
Establish operational objectives and delegate work in ways that develop team members' skills in abuse detection, rate limiting, bot mitigation, and enforcement systems.
Evaluate and communicate tradeoffs between detection coverage, false positive rates, and enforcement aggressiveness to leadership and cross-functional stakeholders.
Foster a team culture of responsible and ethical use of AI and automation tools in building privacy-protective systems.
Actively monitor team performance, provide actionable feedback, and address performance gaps to maintain a high-performing engineering organization.
Represent the anti-scraping team in cross-functional forums, translating complex threat landscapes and technical approaches for non-technical audiences, including legal and policy partners.
Identify and remove barriers that slow detection and enforcement cycles, including simplifying review processes and clarifying decision-making authority across dependent teams.