The opportunity
As a Data Engineer on the Safeguards team, you will build the data foundations that keep our AI systems safe. The Safeguards team works to monitor models, prevent misuse, and ensure user well-being — and doing that well requires robust, reliable data infrastructure.
What you'll do
Design, build, and maintain scalable data pipelines that support safety: monitoring, abuse detection, and enforcement workflows
Develop and optimize data models and warehousing solutions to enable: efficient analysis of large-scale usage and safety data
Build and maintain dashboards and reporting infrastructure that give: Safeguards teams visibility into model behavior, misuse patterns, and enforcement outcomes
Collaborate with engineers to integrate data from multiple sources: including model outputs, user reports, and automated classifiers — into a unified analytical layer
Implement data quality frameworks, monitoring, and alerting to ensure the reliability of safety-critical data
Partner with research teams to surface data insights that inform model improvements and safety interventions
What they're looking for
- + years of experience in data engineering, analytics engineering, or a related role
- Comfort contributing across the stack and picking up work outside your: immediate scope when the situation calls for it
- Background in trust and safety, integrity, fraud, or abuse detection data systems
- Experience with large-scale event streaming systems such as Kafka, Pub/Sub, or Kinesis
- Experience building data infrastructure that supports ML model monitoring or evaluation
- Familiarity with data privacy and compliance frameworks such as GDPR, CCPA, or similar
- Background in statistical analysis or experience working closely with data scientists
- A genuine interest in the societal implications of AI and in making AI systems safer
