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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

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.

What You'll Work On

Depending on your background and interests, you may focus on areas such as:

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 May Be a Good Fit If You:

Have 8+ years of software engineering experience with 3+ years building data infrastructure, storage systems, or related distributed systems
Have deep experience with at least one of:

Cloud data platforms (BigQuery, Redshift, Snowflake) and orchestration tools (Airflow, dbt)
Access control systems, IAM, authentication/authorization at scale
Distributed storage systems, object storage (S3, GCS), disaster recovery

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 expected base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.

Annual Salary:$405,000—$485,000 USD

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

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.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process