About the role

As an Integrity and Authenticity Policy Manager, you will be responsible for developing, refining, and maintaining policies that prevent the misuse of AI systems for deception, manipulation, and unauthorized monitoring at scale. You will serve as the policy owner for risks related to inauthentic behavior, influence activity, surveillance, and the profiling of individuals and groups, and you will help shape policy frameworks across several areas, including authenticity, information integrity, and privacy and surveillance.

Your initial focus will be on translating the Integrity and Authenticity risk framework into clear, enforceable policies, ensuring policy language addresses emerging threats identified by partner teams, and establishing guidelines that enable consistent enforcement decisions. Many of the most serious harms in this space begin with upstream steps that look routine on their own, such as compiling records about a person, automating account creation, or sorting users by inferred identity. Part of your work will be defining where those steps become prohibited. The role will expand as AI capabilities advance. Safety is core to our mission. You will help ensure our products cannot be used to deceive people at scale, monitor and profile people without their knowledge or consent, or sort and target populations based on sensitive characteristics.

Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature, as well as detailed descriptions of privacy violations, surveillance abuses, and deceptive campaigns targeting vulnerable people.

Key responsibilities

• Develop and define policy boundaries for covert monitoring, tracking, and surveillance across different contexts, drawing the distinction between malicious behaviors and compliant dual-use scenarios

• Write policy guidance on facial recognition, voice cloning, and geolocation inference, specifying which uses require consent and which are prohibited outright

• Map the surveillance lifecycle, from target selection and data collection through analysis and covert deployment, and define the policy line at each stage so that interventions can occur early in the chain

• Design and oversee evaluations that measure the model's capability to support social media monitoring, people-finding, predictive profiling, and the identification or tracking of specific people, to build, develop and improve safeguards with cross-functional partners to prevent malicious behaviors

• Write and refine external-facing Usage Policy language and develop training guidelines, assessment rubrics, and evaluation protocols for enforcement teams, with emphasis on indicators of covert monitoring and population-level targeting

• Validate enforcement decisions and automated assessments, provide policy guidance on complex edge cases such as investigative research into surveillance tools, coordinate with civil society, privacy experts, threat intelligence researchers, and academics, and serve as the escalation point for complex integrity and surveillance cases

Minimum qualifications

• Working knowledge of how deceptive campaigns and covert monitoring operate in practice, including account networks, bot operations, data aggregation pipelines, and attribution methods

• Familiarity with surveillance technologies and their misuse, including social media monitoring tools, people-search services, location tracking, spyware, facial recognition, and open-source intelligence techniques used against individuals

• General knowledge of the global regulatory landscape around data protection, privacy, platform regulation, and digital services accountability

• Strong policy writing skills, with the ability to translate complex threat frameworks into clear, enforceable guidelines

• Experience designing policies and workflows that enable both clear human enforcement decision-making and technical implementation in ML classifiers and detection pipelines

• Strong collaboration skills and extensive experience partnering with Engineering, Data Science, Legal, Threat Intelligence, and Policy teams on cross-functional initiatives

• Excellent written and verbal communication skills, with the ability to explain deceptive tactics, surveillance methods, and policy rationales to diverse audiences, including non-specialists and policymakers

Preferred qualifications

• 5+ years of experience in policy development, trust and safety, threat intelligence, or platform integrity, with hands-on work on inauthentic behavior, surveillance-related abuse, or data misuse

• Experience in privacy policy, privacy engineering, or data protection work, including familiarity with privacy impact assessments and data minimization principles

• Experience in intelligence roles, state-aligned monitoring operations, or covert data collection campaigns

• Experience investigating inauthentic networks, covert monitoring, or surveillance abuses at a platform, research organization, or government body

• Background in digital forensics, open-source intelligence, or threat attribution

• Knowledge of persuasion theory, cognitive biases, and deceptive communication techniques, including social engineering and pretexting methods

• Familiarity with human rights and privacy frameworks as they apply to surveillance, including protections for journalists, activists, and marginalized communities

• Experience with trust and safety operations involving content moderation evasion, bot detection, or platform scraping enforcement

• Experience working with EU institutions, regulatory bodies, or policy organizations on AI governance or digital platform regulation

• Experience conducting adversarial testing, red teaming, or vulnerability assessments for AI systems or platforms, particularly for misuse involving monitoring or profiling

• Familiarity with generative AI capabilities and an understanding of how LLMs can be used for synthetic personas, social engineering, predictive profiling, or surveillance at scale