Senior Engineering Analyst, Trust and Safety, Cloud AI

Google
Washington D.C., DC, USA / Seattle, WA, USA

About the job

In this role, you will play a vital role in ensuring that Google Cloud’s Artificial Intelligence (AI) products are not only powerful but also safe, secure, and trustworthy. Your investigative skills, understanding of potential security harms, for user protection will help the teams solve testing problems in AI security and abuse at scale. You will proactively identify and mitigate emerging threats within the AI landscape, ranging from adversarial attacks to potential misuse of generative technologies. You will synthesize large datasets to uncover patterns of abuse, ensuring that Google's AI deployments remain resilient against sophisticated exploitation while upholding our responsibility for safe AI growth.

Responsibilities

Develop and deploy scalable safety solutions for Cloud AI products by leveraging advanced machine learning and AI techniques.

Use data analysis to discover and interpret how attackers exploit Cloud AI infrastructure or use Application Programming Interfaces (APIs) for abuse, identifying weak points in our systems.

Define what constitutes abuse in ambiguous or highly novel AI use cases, ensuring our guidelines adapt to AI-driven attacks.

Analyze and measure generative/agentic AI risks using benchmarking, dataset design, and scaled usage monitoring.

Drive the rapid response for high-priority AI security incidents, conducting through Root Cause Analyses (RCAs) to implement sustainable long-term solutions. Partner with Engineering and Product teams to identify, prioritize, and develop strategies against the most pressing and novel AI threats.

Qualifications

Minimum

Bachelor's degree or equivalent practical experience.

5 years of experience in data analysis or data science, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.

Experience with SQL.

Preferred

Master's degree or PhD in a technical discipline (e.g., Computer Science, Statistics, Mathematics, Operations Research, etc.).

Experience in security threat or abuse detection.

Experience in one domain, such as anomaly detection, security threats analysis and investigation, time-series analysis, Cloud Application Programming Interfaces (APIs), or metrics and reporting.

Understanding of generative AI technologies, Large Language Models (LLMs) and AI agents.

Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.