Security Engineer, Trust & Safety - Applied AI

Meta•Washington, DC

2d•$184,000 - $257,000

About The Position

Meta is seeking Security Engineers with Trust & Safety expertise to join its Applied Artificial Intelligence (AAI) organization. The role applies deep domain expertise in online abuse and adversarial behavior—including child safety, human exploitation, fraud and scams, violent extremism, and coordinated inauthentic behavior—to advance AI capabilities in Trust & Safety. The engineer uses AI tools and agents to accelerate work and applies domain expertise to improve models where they fall short. The work addresses abuse driven by behavior, context, and scale rather than software defects. It includes developing evaluations robust to the gap between public benchmarks and internal challenges, and shaping how AI systems can help prevent and respond to adversarial behavior.

Requirements

B.S. or M.S. in Computer Science, Cybersecurity, or a related field, or equivalent experience.
8+ years of hands-on engineering experience in Trust & Safety, integrity, fraud and abuse, or security investigations.
Deep expertise in at least one abuse domain, with demonstrated ability to advance the state of the art: child safety and youth protection; dangerous organizations and violent extremism; fraud and scams; coordinated inauthentic behavior and information operations; or content policy enforcement.
Experience building detection, enforcement, or evaluation systems in an abuse domain, in addition to operating or investigating within one.
Experience analyzing and interpreting large-scale data, including relational databases and SQL, to identify adversarial behavior patterns and quantify trends.
Experience coding in PHP, Python, Java, or a similar language.
Track record of architecting 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.

Nice To Haves

Experience adversarially testing conversational or agentic systems, including jailbreaks, social engineering, prompt injection, and policy-exception pressure.
Experience authoring or interpreting enforcement guidelines at scale, including coded terminology and evolving slang.
Contributions to the Trust & Safety or security community, such as original research, tools, conference presentations, or publications.
Experience with campaign-level investigation and attribution of coordinated adversary networks.
Ongoing AI skill development, such as prompt or context engineering and agent orchestration, and staying current with emerging AI technologies.
Experience adhering to and implementing responsible, ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews.
Experience developing and evaluating classifiers for abuse, fraud, or policy enforcement.
Experience improving AI model performance through expert feedback, red-teaming, or evaluation design.
Demonstrated ability to integrate AI tools to optimize or redesign workflows and drive measurable impact, such as efficiency gains or quality improvements.
Experience with age assurance and age-signal inference, including calibrated confidence and mode switching.

Responsibilities

Identify and solve ambiguous Trust & Safety problems with initially unknown solutions and requirements, driving solutions that affect multiple teams.
Architect Trust & Safety capabilities and evaluation infrastructure that set standards across teams, and drive platform-level decisions for AI-driven solutions at Meta's scale.
Lead strategy and methodology for abuse problems AI cannot yet reason about, including age-aware policy boundaries, adaptive adversaries, campaign-scale abuse, and policy interpretation under pressure.
Define methodologies that translate Trust & Safety expertise into systematic and scalable model improvement.
Drive cross-organizational partnerships and influence technical direction beyond the immediate team.
Break problems into scoped workstreams, own the most technically complex pieces, and enable others to execute the overall solution.
Mentor engineers across the organization, build community, and model Trust & Safety engineering practices and Meta values.
Share findings through internal publications, knowledge sharing, and contributions to the broader community.