Used Tools & Technologies
Machine LearningRequired Skills & Competences
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.
Kafka @ 3
Python @ 5
SQL @ 5
Looker @ 3
Spark @ 3
Tableau @ 3
dbt @ 3
ETL @ 5
Airflow @ 3
Kinesis @ 3
Communication @ 3
Data Engineering @ 3
ELT @ 5
CCPA @ 2
GDPR @ 2
Fraud @ 3
Reporting @ 3
Snowflake @ 3
Compliance @ 2
AI @ 3
Data Pipelines @ 3
- 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.
Details
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
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.
In this role, you will design and build the 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 directly supports 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
Minimum qualifications
- 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 using tools such as Looker, Tableau, or Metabase
- Ability to communicate clearly and translate complex data concepts for both technical and non-technical audiences
Preferred qualifications
- 8+ 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
Compensation
Annual Salary: $320,000 - $405,000 USD
Logistics
- Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
- Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
- Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
- Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
- Visa sponsorship: We do sponsor visas. We will make every reasonable effort to get you a visa if we make you an offer and retain an immigration lawyer to help.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. We value impact, collaboration, frequent research discussions, and clear communication.
Additional information
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.