Senior Engineering Analyst, Third Party Data Safety

Google•Kirkland, WA

4d•$159,000 - $230,000

About The Position

The Senior Engineering Analyst will work on Google’s Trust and Safety Third-Party Data Safety (3PDS) team, which protects Google’s OAuth ecosystem and user data. The role focuses on scaling defenses through proactive abuse monitoring and post-publication compliance infrastructure. Using an AI-first approach, the analyst will build automated systems and Agentic AI tools to address emerging risks, streamline routine operations, and prevent unauthorized data use. The role involves using Google’s internal AI frameworks to detect threats and govern third-party integrations at scale.

Requirements

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

Nice To Haves

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.

Responsibilities

Architect and build active abuse-monitoring and post-publication compliance pipelines, prioritizing an AI-first approach.
Use 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 identify actionable ecosystem trends, monitor app behavior after verification, and support ongoing policy adherence.
Partner 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 to scale ecosystem governance coverage and efficiency.