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Anthropic Cover

Staff+ Software Engineer, Data Infrastructure

Anthropic
Remote Full Time USD 405,000 - 485,000 p.a. Sep 17, 2026

About the Job

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 syst...

Data Infrastructure designs, operates, and scales secure, privacy-respecting systems that power data-driven decisions across Anthropic. Our mission is to provide data processing, storage, and access that are trusted, fast, and easy to use.

We're looking for infrastructure engineers who thrive working at the intersection of data systems, security, and scalability. You'll tackle diverse challenges ranging from building financial reporting pipelines to architecting access control systems to ensuring cloud storage reliability. This role offers the opportu...

Key Responsibilities

We're looking for infrastructure engineers who thrive working at the intersection of data systems, security, and scalability. You'll tackle diverse challenges ranging from building financial reporting pipelines to architecting access control systems to ensuring cloud storage reliability. This role offers the opportunity to work directly with data scientists, analysts, and business stakeholders while diving deep into cloud infrastructure primitives.
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.
Have 10+ years (not including internships or co-ops) of experience in a Software Engineer role, building data infrastructure, storage systems, or related distributed systems
Have 3+ years (not including internships or co-ops) of experience leading large scale, complex projects or teams as an engineer or tech lead
Can set technical direction for a team, not just execute within it
Have deep experience with at least one of:
Strong proficiency in programming languages like Python, Go, Java, or similar
Experience with infrastructure-as-code (Terraform, Pulumi) and cloud platforms (GCP, AWS)
Can navigate complex technical tradeoffs between performance, cost, security, and maintainability
Have excellent collaboration skills - you work well with both technical and non-technical stakeholders
Experience with security and compliance requirements (ITGC, GDPR, financial controls)
Background in data warehousing, ETL/ELT pipelines, or analytics infrastructure
Experience with Kubernetes, containerization, and cloud-native architectures
Track record of improving data reliability, availability, or cost efficiency at scale
Knowledge of column-oriented databases, OLAP systems, or big data processing frameworks
Experience working in fintech, financial services, or highly regulated environments
Security engineering background with focus on data protection and access controls
Data: BigQuery, BigTable, Airflow, Cloud Composer, dbt, Spark, Segment, Fivetran
Storage: GCS, S3
Infrastructure: Terraform, Kubernetes, GCP, AWS
Languages: Python, Go, SQL

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