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Staff+ Software Engineer, Safeguards Data

Anthropic · San Francisco, CA | New York City, NY

In short

  • ▸Construyes plataformas de datos para sistemas de seguridad de IA con enfoque en integridad y privacidad.
  • ▸Trabajas en pipelines y almacenes de datos en múltiples nubes (AWS, GCP, Azure), con fuerte énfasis en operaciones y portabilidad.
  • ▸El trabajo impacta directamente en la prevención del mal uso de modelos y en el bienestar de los usuarios.
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What they ask for

  • ✓Dominio de Python y SQL
  • ✓Experiencia construyendo e operando pipelines o almacenes de datos en producción
  • ✓Capacidad para trabajar en toda la pila de datos: ingestión, almacenamiento y consumo
  • ✓Habilidades de comunicación escrita y verbal para explicar trade-offs técnicos a no técnicos
  • ✓Enfoque en integridad de datos, retención, control de acceso y privacidad
  • ✓Experiencia con sistemas de datos en entornos multi-nube o diseñados para ser independientes de proveedor

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

PythonSQLAWSGCPAzuredata pipelinesdata storesdata warehousesdata governancedata lineage

Who should you write to at Anthropic?

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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 learning systems • Experience building and operating large-scale distributed data infrastructure • Experience working across multiple cloud providers, or building infrastructure designed to be provider-agnostic • Experience meeting data governance requirements in a regulated or high-sensitivity domain • Experience working closely with operational teams to build custom internal tooling The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. <div

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