About this role
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
We are looking for software engineers to help build safety and oversight mechanisms for our AI systems. As a software engineer on the Safeguards team, you will work to monitor models, prevent misuse, and support user well-being. This role focuses on the data foundations that make that work possible: the pipelines, stores, and governance controls that our detection, evaluation, and review systems are built on, deployed across AWS, GCP, and Azure. You will apply your technical skills to uphold our principles of safety, transparency, and oversight while enforcing our terms of service and acceptable use policies.
The systems you build sit underneath decisions with real consequences for customers and for people affected by model misuse, and much of the data moving through them is sensitive. Correctness, retention discipline, and access control are core engineering requirements here rather than things bolted on afterward. You will also design for portability from the outset, because these systems run in customer-managed and third-party environments you do not fully control.
Key responsibilities
• Build and operate the data platform that powers Safeguards, including ingestion and processing pipelines, warehouses and other data stores, and the schemas and interfaces that detection and review systems depend on
• Keep Safeguards systems running day to day and hold a high operational bar that serves both safety and customers, while reducing the manual effort needed to sustain it
• Own data governance and integrity, including retention and access controls, privacy-preserving handling of sensitive data, lineage, and correctness guarantees that downstream consumers can rely on
• Design systems that run portably across cloud providers, working within the constraints of customer-managed and third-party environments
• Partner with the analysts, investigators, and researchers who rely on this data, and build the internal tooling their work depends on
Minimum qualifications
• Proficiency in Python and SQL
• Experience building and operating data pipelines or data stores in production
• Ability to work across the data stack, including ingestion, storage, and consumption
• Strong written and verbal communication skills, including the ability to explain technical tradeoffs to people outside your discipline
Preferred qualifications
• Extensive experience as a software engineer, including significant time on data-intensive systems
• Experience with integrity, spam, fraud, or abuse detection and mitigation
• Experience building trust and safety detection and intervention mechanisms for AI or machine learn