Senior Engineering Analyst, Third Party Data Safety

About the job

The Trust and Safety Third-Party Data Safety (3PDS) team ensures that Google's OAuth ecosystem and user data remain secure in an increasingly agentic landscape. As a Senior Engineering Analyst, you will play a critical role in scaling our defenses by standing up proactive abuse monitoring and post-publication compliance infrastructure.

Taking an AI-first approach, you will build automated systems and Agentic AI tools to combat emerging risks, streamline routine operations, and protect against unauthorized data usage. This is a unique opportunity to directly leverage Google's AI frameworks to revolutionize how we detect threats and govern third-party integrations at scale. You will be passionate about ecosystem safety and grow on building innovative, scalable solutions, by joining us in securing the future of Google's developer platform.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $159000 - $230000 (USD) + 15% bonus target + equity + benefits

Learn more about

benefits at Google.

Responsibilities

• Architect and stand up active abuse monitoring and post-publication compliance pipelines from scratch, prioritizing an AI-first approach.
• Utilize Google's internal AI frameworks to build Agentic AI solutions that detect novel threats, including indirect prompt injections, unauthorized model training, and API exploitation.
• Analyze complex data sets to extract actionable insights on ecosystem trends, monitor app behavior post-verification, and ensure ongoing policy adherence.
• Partner closely with Identity Engineering, Product, Policy, and Security teams to establish runtime consent gates, automate manifest evaluations, and translate policy requirements into technical enforcement mechanisms.
• Improve Red-team LLM inputs and validate human-in-the-loop systems, scaling coverage and efficiency for ecosystem governance.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 5 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
• 5 years of experience managing projects and defining project scope, goals, and deliverables.

Preferred qualifications:

• Experience architecting, deploying, or operating scalable data pipelines and backend monitoring systems.
• Experience applying AI, ML frameworks, or LLMs to solve complex, ambiguous problems and automate workflows.
• Experience in Trust and Safety, threat intelligence, cybersecurity, or platform compliance, with an understanding of adversarial behaviors and abuse vectors.
• Proficiency in SQL, Python, or similar programming languages for advanced data extraction, manipulation, and analysis.
• Experience translating complex policy requirements into automated technical enforcement mechanisms or runtime consent gates.
• Experience collaborating cross-functionally with engineering, policy, and product teams to drive ecosystem safety and platform integrity initiatives.