Security Engineer, Applied AI

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. 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, cloud security, adversary simulation, forensic investigation, or emerging areas - becomes the foundation for capabilities no existing AI system can replicate.This role is for 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 is capable of.

Required Skills:

Security Engineer, Applied AI Responsibilities:
1. Apply deep security domain expertise to identify, scope, and solve complex security problems that require multi-step reasoning, novel approaches, and expert judgment
2. Build security products, tools, and capabilities - prototyping AI-driven solutions to real-world security challenges at Meta's scale
3. Design and execute adversary research, threat analysis, detection engineering, or investigation workflows augmented by AI tools and agents
4. Identify where AI models lack security reasoning capability and directly contribute to improving them through expert-generated signal, evaluation, and feedback
5. Develop novel methodologies and reusable approaches that advance both Meta's security posture and AI system performance in security domains
6. Collaborate with model researchers to translate security expertise into training signal - decomposing hard problems into structured challenges that teach models to reason like security experts
7. Partner cross-functionally with engineering, product, and research teams to incorporate security innovations into production AI systems
8. Drive end-to-end execution of complex security initiatives with increasing independence, contributing to technical direction within the team
9. Disseminate findings through internal publications, knowledge sharing, and contributions to the broader security community

10. B.S. or M.S. in Computer Science, Cybersecurity, or related field, or equivalent experience. OR PhD + 2 years of hands-on security engineering experience
11. 5+ years of hands-on security engineering experience in one or more domains: detection engineering, threat intelligence, incident response, cloud security, adversary simulation, offensive security, or digital forensics
12. Extensive knowledge of attacker tactics, techniques, and procedures
13. Proficiency in coding with experience in languages such as Python, Go, C/C++, or shell scripting
14. Experience building security systems, tools, or capabilities - not just identifying problems but engineering solutions
15. Demonstrated ability to operate independently on complex, ambiguous security challenges, 16. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
17. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
18. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
19. Experience leveraging AI tools (LLMs, agents, orchestration systems) to accelerate security workflows and enhance operational capability
20. Contributions to the security community (original research, tools, CTF design, conference presentations, publications)
21. Experience creating structured methodologies that scale security expertise across teams
22. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
23. Experience planning and executing adversary simulation campaigns or purple team exercises at scale
24. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
25. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
26. Experience with cloud security operations (AWS/GCP/Azure), cloud detection and response, or cloud-native defense
27. Experience with forensic investigation - reconstructing attack timelines from evidence across multiple sources
28. Background in supply chain security, mobile platform security, network protocol security, or AI/agent security
29. Experience improving AI model performance through expert feedback, red-teaming, or evaluation design