AnthropicSan Francisco, CABuild and scale secure data infrastructure at Anthropic, including access control systems, financial data pipelines, cloud storage reliability, and analytics tooling. Requires 10+ years building data/distributed systems, 3+ years leading complex projects, and deep experience with cloud/IaC or programming languages.
Within Data Infra, you may be matched to critical business areas including:
Data Governance & Access Control: Design and implement robust access control systems ensuring only authorized users can access sensitive data. Build infrastructure for permission management, audit logging, and compliance requirements. Work on IAM policies, ACLs, and security controls that scale across thousands of users and systems.
Financial Data Infrastructure: Build and maintain data pipelines and warehouses powering business-critical reporting. Ensure data integrity, accuracy, and availability for complex financial systems, including third party revenue ingestion pipelines; manage the external relationships as needed to drive upstream dependencies. Own the reliability of systems processing revenue, usage, and business metrics.
Cloud Storage & Reliability: Architect disaster recovery, backup, and replication systems for petabyte-scale data. Ensure high availability and durability of data stored in cloud object storage (GCS, S3). Build systems that protect against data loss and enable rapid recovery.
Data Platform & Tooling: Scale data processing infrastructure using technologies like BigQuery, BigTable, Airflow, dbt, and Spark. Optimize query performance, manage costs, and enable self-service analytics across the organization.
Build and operate production data pipelines, observability tools, and planning systems to maximize utilization, efficiency, and attribution of Anthropic's large-scale multi-cloud accelerator and CPU fleet. Requires strong Python/SQL, cloud operations, and Kubernetes experience in a high-ambiguity environment.
Build and scale the core database infrastructure powering Claude at Anthropic, including data plane/control plane, data movement (CDC, migrations), and caching systems that support millions of users and frontier AI research across multi-cloud environments. Requires deep expertise in distributed databases and production storage systems.
Architect and build Voleon’s batch and realtime streaming platform that powers ML research and production trading systems. Requires 10+ years experience building scalable data infrastructure with Python, Go, and distributed systems.
Research Engineer owning datasets for training world simulation AI models, designing multimodal datasets, running experiments, and building data pipelines to enhance model capabilities across tasks like robotics and creative tools. Requires 4+ years in ML with experience in generative models and frameworks like PyTorch or JAX.
Leads architecture and development of large-scale data platforms for AI, including storage, streaming, caching, and indexing. Requires 8+ years experience with databases, streaming tools, Kubernetes, and distributed systems.