Staff+ Software Engineer, Data Infrastructure

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

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.

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.

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. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

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.

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.