Security Engineer - Applied AI
Meta
- Location
- Onsite (London, England)
- Employment
- Full-time
- Level
- Senior Level
Posted 2 days ago
About the Role
Meta's Applied AI organization is seeking a Security Engineer to architect and implement AI-driven security systems. The role focuses on solving complex security challenges through adversarial research, detection strategies, and scalable AI-native systems to enhance Trust and Safety.
Skills
Security Engineering
Artificial Intelligence
Machine Learning
Detection Engineering
Threat Intelligence
Adversarial Analysis
Cloud Security
Offensive Security
Digital Forensics
Python
Rust
Adversary Simulation
Trust and Safety
System Architecture
Risk Assessment
Red Teaming
Full job details
Meta is seeking Security Engineers to join our Applied Artificial Intelligence (AAI) organization. As a Security Engineer in AAI, you will apply deep domain expertise to solve hard, real-world security problems, building novel security capabilities, prototyping AI-powered defenses, and advancing the frontier of what AI systems can do in Security, Trust, and Safety. Your work is AI-augmented from day one: you leverage AI tools and agents to accelerate your impact, and where the models fall short, your expertise directly drives their improvement.
You will blend hands-on security engineering with applied research: designing and executing novel approaches to security challenges that push both the state of Meta's security posture and the state of the art in AI-driven security. This includes building security products and tools, conducting original adversary research, developing detection and response capabilities, and translating security expertise into scalable, AI-native systems. Your domain knowledge — whether in detection engineering, threat intelligence and adversarial analysis, cloud security, adversary simulation, mobile and platform security, forensic investigation, or emerging areas like AI/ML security — becomes the foundation for capabilities no existing AI system can replicate.
This role is for experienced security practitioners who want to operate at the intersection of deep security expertise and frontier AI — not just using AI as a tool, but shaping what it becomes.
Responsibilities
- Identify and solve ambiguous problems within a Security, Trust, or Safety domain where the solution and requirements are initially unknown, driving solutions that affect multiple teams
- Architect security systems and capabilities that set the standard across teams; drive platform-level decisions for AI-driven security solutions at Meta's scale
- Lead the strategy and methodology for adversarial research, threat intelligence programs, detection systems, or investigation capabilities augmented by AI
- Shape how security expertise translates into AI capability: define the methodologies that make model improvement systematic and scalable
- Set and improve quality standards for security engineering practices and processes across teams; define processes and workflows that achieve scale and automation
- Drive cross-organizational partnerships that define how security and AI intersect: influence technical direction beyond the immediate team
- Break down problems into smaller, scoped workstreams, owning the most technically complex pieces while enabling others to execute against the overall solution
- Mentor other engineers across the organization, build a community, and act as a role model for security engineering practices and Meta values
- Drive team-wide adoption of practices and standards; proactively communicate updates to leadership audiences
- Disseminate findings through internal publications, knowledge sharing, and contributions to the broader security community
Minimum Qualifications
- B.S. or M.S. in Computer Science, Cybersecurity, or a related field, or equivalent experience
- 8+ years of hands-on security engineering experience in one or more domains: detection engineering, threat intelligence, incident response, cloud security, adversary simulation, offensive security, mobile/platform security, digital forensics, trust and safety
- Deep expertise in attacker tactics, techniques, and procedures with demonstrated ability to advance the state of the art
- Proficiency in coding with experience in languages such as Python or Rust
- Track record of architecting security systems or programs that operate at scale and influence how others build
- Demonstrated ability to define and drive complex, ambiguous problem spaces with group-level impact
- Experience in driving alignment and resolution across multiple teams and cross-functional partners
Preferred Qualifications
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Contributions to the security community (original research, tools, conference presentations, publications)
- Experience improving AI model performance through expert feedback, red teaming, or evaluation design
- Experience with cloud security operations, cloud detection and response, or cloud-native defense
- Experience in hands on investigations across the Trust & Safety domain
- Experience with forensic investigation — reconstructing attack timelines from evidence across multiple sources
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
- Experience in planning and executing adversary simulation campaigns or purple team exercises at scale
- Experience leveraging AI tools to accelerate security workflows and enhance operational capability
- Experience in creating structured methodologies that scale security expertise across teams
- Background in supply chain security, mobile platform security, network protocol security, or AI/ML security