Anthropic· Safeguards (Trust & Safety) · London, UK
Data Engineer, Safeguards
Classified Tasks (11)
Automate 0%Augment 100%Human-Only 0%
Augment (11)
AI assists, human decides
Design scalable data pipelines to support safety monitoring, abuse detection, and enforcement workflows
technical
Build and maintain scalable data pipelines that support safety monitoring, abuse detection, and enforcement workflows
technical
Develop and optimize data models to enable efficient analysis of large-scale usage and safety data
technical
Implement and maintain warehousing solutions to enable efficient analysis of large-scale usage and safety data
technical
Build and maintain dashboards and reporting infrastructure that surface model behavior, misuse patterns, and enforcement outcomes
technical
Collaborate with engineers to integrate data from model outputs, user reports, and automated classifiers into a unified analytical layer
operational
Implement data quality frameworks, monitoring, and alerting to ensure the reliability of safety-critical data
technical
Partner with research teams to surface data insights that inform model improvements and safety interventions
communication
Develop self-service data tooling that enables stakeholders to explore safety data and generate reports independently
technical
Contribute to data governance practices, including implementing access controls, retention policies, and privacy-compliant data handling
administrative
Provide data and analytical support to detect abuse patterns, measure the effectiveness of safety interventions, and inform decisions about model behavior and enforcement
analytical
Job description
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is looking for a Data Engineer to join the Safeguards team and 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. In this role, you'll design and build the data pipelines, warehousing solutions, and analytical tooling that power our safety and trust efforts at scale. You'll work closely with engineers, data scientists, and policy teams to ensure the Safeguards organization has the data it needs to detect abuse patterns, measure the effectiveness of safety interventions, and make informed decisions about model behavior and enforcement. This is a high-impact role where your work will directly support Anthropic's mission to develop AI that is safe and beneficial. Responsibilities: - 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 - Develop self-service data tooling that enables stakeholders to explore safety data and generate reports independently - Contribute to data governance practices, including access controls, retention policies, and privacy-compliant data handling You may be a good fit if you: - Have 3+ years of experience in data engineering, analytics engineering, or a related role - Are proficient in SQL and Python, with experience building and maintaining ETL/ELT pipelines - Have hands-on experience with modern data stack tools such as dbt, Airflow, Spark, or similar orchestration and transformation frameworks - Have worked with cloud data platforms (BigQuery, Redshift, Snowflake, or similar) - Are comfortable building dashboards and data visualizations using tools like Looker, Tableau, or Metabase - Communicate clearly and can translate complex data concepts for both technical and non-technical audiences - Are results-oriented, flexible, and willing to pick up slack even when it falls outside your job description - Care about the societal impacts of AI and are motivated by safety work Strong candidates may have: - Experience with trust & safety, integrity, fraud, or abuse detection data systems - Experience with large-scale event streaming systems (Kafka, Pub/Sub, Kinesis) - Built data infrastructure that supports ML model monitoring or evaluation - Familiarity with data privacy and compliance frameworks (GDPR, CCPA, or similar) - A background in statistical analysis, or experience collaborating closely with data scientists - Developed internal tooling or self-service analytics platforms Strong candidates need not have: - A fo