Senior Engineering Analyst, Third Party Data Safety

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.

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.