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Open nowFirst seen 8 hours ago

Security Engineering Manager, Anti-Scraping

Meta1,224 open roles

Where
Menlo Park, CA
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Your applicationOpen nowSecurity Engineering Manager, Anti-ScrapingMeta · Menlo Park, CA

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The clock on this job

Early applications get read.

12.8% of postings close within 7 days. Measured by our own scanner across the market. Meta postings stay open a median of 35 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.5%3 days
  3. 12.8%7 days
  4. 20.6%14 days
  5. 35.6%30 days
  6. 58.4%60 days
This job: first seen 8 hours ago

Meta median: 35 days open

The posting

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.

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

Minimum 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
  • BS in Computer Science or equivalent experience in Security

Preferred Qualifications

  • 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

US: $184,000/year to $257,000/year + bonus + equity

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