Privacy Security Engineer, Privacy & Data Protection - Applied AI

Meta is seeking Security Engineers with Privacy and Data protection expertise to join our Applied Artificial Intelligence (AAI) organization. You will apply deep privacy engineering expertise to hard, real-world problems in how systems collect, use, retain, expose, and delete data. 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.The problems that matter here are the ones a capable engineer cannot solve by reading the code in front of them: which jurisdiction's deadline applies to a deletion request, whether a derived dataset clears an anonymity threshold, where a deletion has to cascade. Models already handle the privacy obligations that are stated as ordinary good engineering practice, so the work is the obligation they cannot derive.This role is for privacy engineers who want to operate at the intersection of deep privacy expertise and frontier AI, not just applying AI to privacy work but shaping what it is capable of.Privacy Security Engineer, Privacy & Data Protection - Applied AI Responsibilities:Apply deep privacy and data protection expertise to identify, scope, and solve complex problems that require multi-step reasoning, novel approaches, and expert judgmentBuild privacy capabilities, tools, and evaluation environments, prototyping AI-driven solutions to real-world privacy problems at Meta's scaleDesign and execute privacy obligation analysis, de-identification assessment, data lifecycle review, or data access reasoning augmented by AI tools and agentsIdentify where AI models lack privacy reasoning capability and directly contribute to improving them through expert-generated signals, evaluation, and feedbackCollaborate with model researchers to translate privacy expertise into training signals, decomposing hard problems into structured challenges that teach models to reason like privacy engineersPartner with legal, policy, product, and infrastructure teams to translate obligations into engineering requirementsOwn complex privacy initiatives end to end, from problem definition through delivery, and contribute to technical direction within the teamDisseminate findings through internal publications, knowledge sharing, and contributions to the broader privacy and security communityMinimum Qualifications:B.S. or M.S. in Computer Science, Cybersecurity, or related field, or equivalent experience5+ years of hands-on engineering experience in technical privacy, data protection, or privacy-adjacent security engineeringDeep expertise in at least one privacy subdomain with demonstrated ability to advance the state of the art: purpose limitation, retention and deletion, data access control, jurisdictional obligations, de-identification, consent, or ML and model privacyExperience implementing privacy obligations in production systems, in addition to reviewing or advising on themSoftware engineering proficiency, including code review and maintenance, with experience coding in Python, PHP, Java, C/C++, or an equivalent languageTrack record of architecting privacy systems, controls or programs that operate at scale and influence how others buildDemonstrated ability to define and drive complex, ambiguous problem spaces with group-level impactPreferred Qualifications:Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologiesExperience applying differential privacy, k-anonymity, or other formal de-identification techniques in production rather than in research onlyExperience with pseudonymization lifecycle, including deletion of the user-to-pseudonym mappingExperience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)Experience implementing obligations conditioned on jurisdiction, age band, or cohort: regional carve-outs, regulatory deadlines, minor and parent-initiated request handlingExperience improving AI model performance through expert feedback, red teaming, or evaluation designBackground in ML and model privacy: memorization, membership inference, training-data extractability, disclosure through model outputsDemonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)Contributions to the privacy or security community (original research, tools, conference presentations, publications)Experience with privacy review or privacy incident response at scaleAbout Meta:Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
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