Engineering Analyst, Trust and Safety, Intel Collections

Google
Austin, TX, USA

About the job

As a member of the T&S Intel Collection team, your mission is to detect new abuse threats and vulnerabilities, triage and enrich signals, and share with teams for action, supporting teams working on new and existing Google products. The Engineering Analyst will drive crucial AI and automation efforts to scale internal tooling, specifically by building the infrastructure that powers our threat discovery through external data integration and automated detection systems. You will architect and implement technical solutions using scripting languages, database design, and system architecture to optimize daily workflows. You'll serve as a critical technical bridge across intel and core engineering teams to ensure operational needs align seamlessly with broader strategic goals. In addition, you will translate complex system capabilities into actionable strategies, advocating for AI adoption and educating cross-functional stakeholders to drive long-term organizational efficiency.

Responsibilities

Build and maintain automated data pipelines, reporting dashboards, and reusable frameworks. This competency includes the skill to gather requirements from non-technical stakeholders and transform raw data into clear, actionable visualizations and reports.

Act as a crucial link between intelligence analysts and product, engineering, and policy teams. This includes communicating effectively with intel analysts and collaborating to ensure their outputs are integrated into product features and enforcement systems, and creating feedback loops that inform system improvements.

Develop and refine prompt sets for large language models to leverage AI models through automation to maximize workflows.

Conduct quality checks and data validation to ensure the accuracy and integrity of all data and prompts used in production systems. This role works with sensitive content or situations and may be exposed to graphic, controversial, and/or upsetting topics or content.

Qualifications

Minimum

Bachelor's degree or equivalent practical experience.

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

2 years of experience managing projects and defining project scope, goals, and deliverables.

Preferred

Master's degree in a quantitative discipline.

2 years of experience or familiarity with one or more of the following languages: SQL, R, Python, or C++.

2 years of experience or familiarity with machine learning systems.

Excellent written and verbal communication skills.

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