Policy Development Lead, YouTube Trust and Safety

About the job

Fast-paced, dynamic, and proactive, YouTube’s Trust and Safety team is dedicated to making YouTube a safe place for users, viewers, and content creators around the world to create, and express themselves. Whether understanding and solving their online content concerns, navigating within global legal frameworks, or writing and enforcing worldwide policy, the Trust & Safety team is on the frontlines of enhancing the YouTube experience, building internet safety, and protecting free speech in our ever-evolving digital world.

As a part of the Adversarial Abuse Policy Development team within Trust and Safety, you will operate on the front lines of platform defense. You will not play by traditional rules but rapidly adapt to our defenses, executing coordinated spam campaigns, synthetic media impersonations, and sophisticated monetization scams. As a Policy Development Lead for AI and Adversarial Integrity, you will lead global policy frameworks that address the dual frontier of Artificial Intelligence. You will design durable, machine-enforceable policies to detect and mitigate malicious uses of generative AI, including evasive botnets, mass-produced synthetic slop, and deepfake impersonations. You will pioneer the use of internal generative AI and Large Language Model (LLM) tooling to analyze complex threat patterns, stress-test policy boundaries, and prototype enforcement frameworks at YouTube scale.

In this role, you will act as the critical bridge between behavioral threat analysis, machine learning engineering, operations, and product strategy. You will unpack adversarial business models and author robust enforcement guidelines that safeguard the YouTube ecosystem.At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $136000 - $196000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Lead the end-to-end development, implementation, and life-cycle governance of global policies targeting scaled adversarial abuse, generative AI exploitation, coordinated spam networks, and inorganic platform manipulation.
• Analyze malicious actor strategies, incentives, and evasion techniques to develop policy architectures that mitigate widespread abuse.
• Partner directly with Engineering, Data Science, and Product Management to translate nuanced policy principles into machine-enforceable heuristics and automated enforcement workflows.
• Serve as the subject matter expert on adversarial abuse, briefing cross-functional executives, Legal counsel, Public Policy, and others on emerging threat vectors, high-profile investigations, and long-term ecosystem defense.
• Design and maintain clear enforcement guidelines and operational workflows for global review teams, balancing safety and creator needs.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 5 years of experience in a policy, legal, trust and safety, or technology environment.
• Experience with the development, implementation, and maintenance of policy.

Preferred qualifications:

• Experience developing anti-abuse, platform integrity, cybersecurity, or fraud policies targeting coordinated bad actors, spam networks, or scaled platform manipulation.
• Experience conducting adversarial threat modeling, red-teaming, or reverse engineering bad-actor business models, circumvention tactics, and technical exploits.
• Experience working with engineering and analytics teams to co-develop automated detection pipelines or signal heuristics.
• Experience analyzing datasets to ground policy recommendations in empirical evidence.
• Experience translating technical concepts into clear guidelines and executive-level presentations.
• Familiarity with modern machine learning and generative artificial intelligence architectures, including synthetic audio or video generation.

• Bachelor's degree or equivalent practical experience.
• 5 years of experience in a policy, legal, trust and safety, or technology environment.
• Experience with the development, implementation, and maintenance of policy.