Staff+ Software Engineer, Data Infrastructure

Anthropic; New York (NY); Hybrid; USD 405,000 - 485,000; Full time

Benefits offered by this job

Competitive compensation

Equity donation matching

Generous vacation

Parental leave

Flexible working hours

Job summary

Anthropic is seeking an experienced Data Infrastructure engineer to design, operate, and scale secure, privacy-respecting data systems across the organization. You will collaborate with data scientists, analysts, and business stakeholders to power data-driven decisions and trustworthy AI initiatives.

In this hybrid role, you will own data governance, build robust pipelines and warehouses for financial metrics, ensure cloud storage reliability, and scale data processing with tools like BigQuery,

Qualifications

• 10+ years of experience in a Software Engineer role building data infrastructure or distributed systems.
• 3+ years leading large-scale projects or teams as an engineer or tech lead.
• Proficiency in Python, Go, Java or similar languages.
• Experience with infrastructure-as-code (Terraform, Pulumi) and cloud platforms (GCP, AWS).
• Ability to balance performance, cost, security, and maintainability.
• Strong collaboration with technical and non-technical stakeholders.

Responsibilities

• Data Governance & Access Control: design and implement robust access control systems with audit logging and compliance.
• Financial Data Infrastructure: build and maintain data pipelines and warehouses powering reporting and metrics.
• Cloud Storage & Reliability: architect disaster recovery, backup, and replication for cloud data.
• Data Platform & Tooling: scale processing using BigQuery, BigTable, Airflow, dbt, and Spark.

Skills

Python

Go

Java

Distributed systems

Education

Bachelor’s degree

Tools

Terraform

Pulumi

Kubernetes

BigQuery

Airflow

dbt

Job description

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 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

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.

Annual Salary: $405,000—$485,000 USD

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

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.

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.