Data Engineer, Safeguards

at Anthropic

📍 New York City, United States
📍 San Francisco, United States

USD 320,000-405,000 per year

MIDDLE

✅ Hybrid

✅ Visa Sponsorship

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 3 Airflow @ 3 CCPA @ 2 Compliance @ 2 Data Engineering @ 3 Data Pipelines ELT @ 5 ETL @ 5 Fraud @ 3 GDPR @ 2 Kafka @ 3 Kinesis @ 3 Looker @ 3 Machine Learning @ 3 Python @ 5 SQL @ 5 Snowflake @ 3 Spark @ 3 Tableau @ 3 dbt @ 3

Details

Anthropic's Safeguards team is seeking a Data Engineer to build the data foundations that support AI safety. The role focuses on developing reliable data infrastructure for safety monitoring, abuse detection, enforcement workflows, model behavior analysis, and user well-being efforts.

Responsibilities

Design, build, and maintain scalable data pipelines for safety monitoring, abuse detection, and enforcement workflows.
Develop and optimize data models and warehousing solutions for large-scale usage and safety data.
Build and maintain dashboards and reporting infrastructure covering model behavior, misuse patterns, and enforcement outcomes.
Integrate data from model outputs, user reports, and automated classifiers into a unified analytical layer.
Implement data quality frameworks, monitoring, and alerting for safety-critical data.
Partner with research teams to surface insights that inform model improvements and safety interventions.
Develop self-service data tooling for exploring safety data and generating reports.
Contribute to data governance practices, including access controls, retention policies, and privacy-compliant data handling.

Requirements

Proficiency in SQL and Python, with hands-on experience building and maintaining ETL/ELT pipelines.
Experience with cloud data platforms such as BigQuery, Redshift, Snowflake, or similar.
Experience with modern data stack tools such as dbt, Airflow, Spark, or similar orchestration and transformation frameworks.
Experience building dashboards and data visualizations with tools such as Looker, Tableau, or Metabase.
Ability to communicate clearly and explain complex data concepts to technical and non-technical audiences.
Bachelor's degree or an equivalent combination of education, training, and experience in a relevant field.

Preferred Qualifications

8 or more years of experience in data engineering, analytics engineering, or a related role.
Experience with 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 for machine learning model monitoring or evaluation.
Familiarity with data privacy and compliance frameworks such as GDPR or CCPA.
Background in statistical analysis or close collaboration with data scientists.
Comfort contributing across the stack and working outside one's immediate scope.
Interest in the societal implications of AI and making AI systems safer.

Benefits

Anthropic offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office space for collaboration. Staff are currently expected to work from an Anthropic office at least 25% of the time.