Software Engineer, Infrastructure (Technical Leadership) - Central Security

You'll be joining Central Security, Meta's first line of defense technology team, managing risk across critical security domains. You'll work within a cross-functional team of engineers, analysts, product managers and program managers, collaborating closely with colleagues across Product, Infrastructure and Enterprise Engineering. You will develop automated and autonomous security systems using AI/ML across high-impact the product security domains. The organization operates at the intersection of cutting-edge technology and enterprise security, helping shape how Meta approaches security across our entire technology stack, from custom-built systems to commercial software such as cloud services, and increasingly sophisticated AI/ML systems.
Work in this organization includes embedding secure-by-design principles across the AI/ML lifecycle from conception to deployment, and identifying, assessing and mitigating security risks unique to AI/ML systems and the products built on them: classical ML, agentic product features, and frontier models. You will help navigate the tradeoffs between security requirements and operational friction so that Meta can maintain its pace of innovation while remaining secure.

Responsibilities

• Drive the team's goals and technical direction to pursue opportunities that make your larger organization more efficient.
• Effectively communicate complex features and systems in detail.
• Understand industry & company-wide trends to help assess & develop new technologies.
• Partner & collaborate with organization leaders to help improve the level of performance of the team & organization.
• Identify new opportunities for the larger organization & influence the appropriate people for staffing/prioritizing these new ideas.
• Lead long term technical vision and roadmap for large cross-company efforts.
• Suggest, collect and synthesize requirements and create an effective feature roadmap.
• Identify and resolve performance and scalability issues, and drive large efforts to reduce technical debt.

Minimum qualifications

• 12+ years of programming experience in a relevant language OR 8+ years experience with a PhD
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Experience mentoring/influencing executive stakeholders across organizations
• Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions
• Experience communicating and working across functions to drive solutions
• Proven track record of planning multi-year roadmap in which short-term projects ladder to the long-term mission
• Experience driving large cross-functional/industry-wide engineering efforts Experience in programming languages such as C, C++, or Java, and scripting languages such as Python, Javascript, or Hack
• 8+ years relevant experience building large-scale infrastructure applications or similar experience
• Experience improving quality through thoughtful code reviews, appropriate testing, proper rollout, monitoring, and proactive changes
• 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
• Demonstrated curiosity about security — e.g., a track record of reasoning about failure modes, abuse cases, or threat models in systems you've built, without requiring prior formal security experience

Preferred qualifications

• Experience in programming languages such as C, C++, or Java, and scripting languages such as Python, Javascript, or Hack
• 8+ years relevant experience building large-scale infrastructure applications or similar experience
• Experience improving quality through thoughtful code reviews, appropriate testing, proper rollout, monitoring, and proactive changes
• 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
• Demonstrated curiosity about security — e.g., a track record of reasoning about failure modes, abuse cases, or threat models in systems you've built, without requiring prior formal security experience