Privacy Engineer, Implementation Review

Meta's Privacy Engineering organization is seeking a passionate engineer to identify, advise, investigate, and mitigate privacy violations and/or exposures in our products. Your skills will be the foundation for understanding privacy risks in Meta initiatives by being the technical advocate for privacy decisions and discussions across the company. You will be relied upon to provide engineering and product teams with the privacy expertise necessary to make confident product decisions.

Responsibilities

• Play a key role in driving code and architecture reviews, as well as large cross-company privacy reviews of products and features
• Conduct technical reviews for new features and identify privacy concerns. Work closely with technical and non-technical teams, including Engineering, Product and Legal
• Provide product teams with the guidance and best practices to help protect users' privacy and mitigate any risk. Work closely with Security and Privacy leaders to help define goals that are properly aligned to the company-wide goals
• Define and articulate a clear vision for privacy, and influence leaders across all of Meta to adopt a balanced view of product and privacy goals in overall decision-making

Minimum Qualifications

• 5+ years of work experience in technical privacy, security, or software engineering, with a focus on designing and developing privacy or security-sensitive systems
• 2+ years of work experience coding in Python, PHP, Java, C/C++ (or an equivalent language), including code maintenance and review
• B.S. or M.S. in Computer Science or a related field or equivalent relevant technical experience Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Technical contributions to the privacy or security community (e.g., public research, blogging, presentations)
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Experience within a corporate environment, communicating technical issues and their implications to other areas of the business