Location
London

Hours
Full Time

Salary
Negotiable

About the Role
Meta is seeking Security Engineers with deep Privacy and Data Protection expertise to join our Applied Artificial Intelligence (AAI) organization. In this role, you will apply advanced privacy engineering skills to complex, real-world challenges involving how systems collect, use, retain, expose, and delete data. Your work is AI-augmented from day one: leveraging AI tools and agents to accelerate your impact, while using your expertise to improve the models where they fall short. You will tackle problems that require more than code review, such as determining jurisdictional deadlines for deletion requests, assessing anonymity thresholds for derived datasets, and managing cascading deletions.

This role is ideal 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 AI is capable of. You will identify and solve ambiguous privacy and data protection problems where solutions and requirements are initially unknown, architect privacy capabilities and evaluation infrastructure that set standards across teams, and drive platform-level decisions for AI-driven privacy solutions at Meta's scale.

You will lead strategy and methodology for privacy challenges AI cannot yet reason about, including jurisdictional and regulatory obligations, de-identification standards, data lifecycle controls, and data access reasoning. You will shape how privacy expertise translates into AI capabilities by defining methodologies that make model improvement systematic and scalable. Additionally, you will drive cross-organizational partnerships to influence the technical direction where privacy and AI intersect.

Responsibilities include breaking down complex problems into manageable work streams, owning the most technically challenging pieces, mentoring engineers, building a community, and acting as a role model for privacy engineering practices and Meta values. You will disseminate findings through internal publications, knowledge sharing, and contributions to the broader privacy and security community.

Experience
- 8+ years of hands-on engineering experience in technical privacy, data protection, or privacy-adjacent security engineering
- Deep expertise in at least one privacy subdomain such as purpose limitation, retention and deletion, data access control, jurisdictional obligations, de-identification, consent, or ML and model privacy
- Experience implementing privacy obligations in production systems and reviewing or advising on them
- Proficiency in software engineering including code review and maintenance, with experience coding in Python, PHP, Java, C/C++, or equivalent languages
- Proven track record of architecting privacy systems, controls, or programs that operate at scale and influence others
- Demonstrated ability to define and drive complex, ambiguous problem spaces with group-level impact
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Experience improving AI model performance through expert feedback, red teaming, or evaluation design
- Experience with pseudonymization lifecycle including deletion of user-to-pseudonym mappings
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact
- Ongoing AI skill development including prompt/context engineering and agent orchestration
- Experience implementing obligations conditioned on jurisdiction, age band, or cohort such as regional carve-outs, regulatory deadlines, and minor/parent-initiated request handling
- Contributions to the privacy or security community through original research, tools, conference presentations, or publications
- Experience applying differential privacy, k-anonymity, or other formal de-identification techniques in production
- Experience with privacy review or privacy incident response at scale
- Background in ML and model privacy including memorization, membership inference, training-data extractability, and disclosure through model outputs

About you
You are a highly skilled privacy engineer passionate about solving ambiguous and complex privacy problems at scale. You thrive at the intersection of privacy and AI, eager to shape the future of AI-driven privacy solutions. You are a collaborative mentor and community builder who upholds Meta’s values and drives technical excellence across teams. You stay current with emerging AI technologies and are committed to responsible and ethical AI practices.

Qualifications
B.S. or M.S. in Computer Science, Cybersecurity, or a related field, or equivalent experience