Data Engineer (AI)

TL;DR

Data Engineer (AI): Build and maintain scalable data pipelines, warehousing solutions, and analytical tools to support AI safety and safeguards. Focus on designing robust data infrastructure for abuse detection, safety monitoring, and enforcement workflows at scale.

Location: San Francisco, CA or New York City, NY with hybrid work format requiring office presence at least 25% of the time. Work authorization or visa sponsorship available but not guaranteed for all candidates.

Salary: $320,000 - $405,000 USD annually.

Company

Anthropic is a public benefit corporation focused on creating reliable, interpretable, and steerable AI systems that are safe and beneficial for society.

What you will do

• Design, build, and maintain scalable data pipelines supporting safety monitoring and abuse detection.
• Develop and optimize data models and warehousing solutions for large-scale safety data analysis.
• Create dashboards and reporting infrastructure for visibility into model behavior and enforcement outcomes.
• Integrate data from multiple sources into unified analytical layers collaborating with engineers and data scientists.
• Implement data quality frameworks, monitoring, and alerting to ensure data reliability.
• Contribute to data governance including access controls, retention policies, and privacy compliance.

Requirements

• Location: Must be based in or able to work from San Francisco or New York City with hybrid office attendance.
• Proficiency in SQL and Python with experience building ETL/ELT pipelines.
• Experience with cloud data platforms like BigQuery, Redshift, or Snowflake.
• Familiarity with data orchestration tools such as dbt, Airflow, or Spark.
• Experience building dashboards using Looker, Tableau, or Metabase.
• Ability to communicate complex data concepts to technical and non-technical audiences.

Nice to have

• 8+ years of experience in data engineering or analytics engineering.
• Background in trust and safety, fraud, or abuse detection data systems.
• Experience with event streaming systems like Kafka or Pub/Sub.
• Knowledge of data privacy frameworks such as GDPR or CCPA.
• Interest in societal implications of AI and AI safety.

Culture & Benefits

• Competitive compensation and benefits including optional equity donation matching.
• Generous vacation and parental leave policies.
• Flexible working hours and hybrid work environment.
• Supportive and collaborative team culture focused on impactful AI research.
• Visa sponsorship available with immigration legal support.