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
- 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 opportunity to work directly with data scientists, analysts, and business stakeholders while diving deep into cloud infrastructure primitives.
Responsibilities
- 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.
You might be a good fit if you
- Have 6+ years (not including internships or co-ops) of experience in a Software Engineer role, building data infrastructure, storage systems, or related distributed systems
- Have 1+ years (not including internships or co-ops) of experience leading large scale, complex projects or teams
- 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
- Are comfortable with ambiguity and can independently scope and drive large projects
Strong candidates may also have
- 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
Technologies We Use
- Data: BigQuery, BigTable, Airflow, Cloud Composer, dbt, Spark, Segment, Fivetran
- Storage: GCS, S3
- Infrastructure: Terraform, Kubernetes, GCP, AWS
- Languages: Python, Go, SQL
Deadline to apply: None. Applications will be reviewed on a rolling basis.
- 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.
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. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
- The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
