Security Engineering Manager, Anti-Scraping

Meta; Menlo Park (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Meta seeks a Security Engineering Manager to lead our Anti-Scraping engineering team within Privacy Engineering. You will guide a team building scalable anti-scraping infrastructure, collaborate with Privacy, Security, Legal, and Product teams, and define roadmaps to detect and mitigate scraping threats at scale.

The role emphasizes leadership, cross-functional influence, and integrating AI to optimize detection workflows while ensuring responsible AI practices and regulatory alignment.

Qualifications

• 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.
• Demonstrated ability to integrate AI tools to optimize detection workflows and drive measurable improvements in coverage or enforcement efficiency.
• 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 (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 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.

Skills

Security leadership

Threat detection

Bot mitigation

AI/ML in security

Stakeholder communication

Privacy frameworks

Adversarial systems

Machine learning

Team management

Data privacy

Education

BS in Computer Science

Job description

Meta is seeking a Security Engineering Manager to lead our Anti‑Scraping engineering team within the Privacy Engineering organization. Scraping poses a significant threat to user privacy, platform integrity, and data security across Meta's family of apps, and this team builds the detection systems, enforcement pipelines, and adversarial defenses that protect billions of users from unauthorized data collection. In this role, you will lead a team of engineers developing scalable anti‑scraping infrastructure, working at the intersection of privacy engineering, threat detection, and abuse prevention. You will partner closely with Privacy, Security, Legal, and Product teams to define strategy, drive technical roadmaps, and deliver systems that proactively identify and mitigate scraping threats at scale.

• 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
• 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/redesign workflows and drive measurable impact (e.g., efficiency gains, 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 (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 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