Staff+ Software Engineer, Databases

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.

We're looking for experienced engineers to build and scale the database infrastructure that powers Claude's products and Anthropic's research. As a Software Engineer on the Databases team, you'll architect and operate the systems that let millions of users interact with Claude while also supporting frontier AI research workloads.

You'll help set the database strategy for Anthropic: designing systems that handle billions of API requests, building storage that runs cleanly across GCP, AWS, and a range of deployment models, and creating the reliable data layer that lets research move fast.

The Databases team spans three areas: the core database platform (data plane and control plane), data movement (migrations, backfill, and change data capture), and caching. We're hiring across all three.

Key Responsibilities

Minimum Qualifications

• Drive the technical direction for database solutions used across Product and Research
• Design and implement database solutions that scale to support millions of users across Claude's product ecosystem
• Build and scale database systems through 100x+ growth while maintaining reliability and performance
• Build the database platform that lets Anthropic engineers ship without thinking about databases or scaling.
• Architect data storage solutions that operate across GCP, AWS, first-party deployments, third-party deployments, and other environments
• Develop database infrastructure that serves both product and research workloads with different performance characteristics
• Build data movement infrastructure (migration tooling, backfill, and change data capture pipelines) that safely consolidates and moves data across the organization
• Design and operate caching infrastructure, including CDC-driven cache invalidation, that keeps Anthropic's hottest paths fast and correct
• Partner with product and research teams to understand data requirements and build infrastructure that accelerates their work
• Optimize database performance, reliability, and cost efficiency at scale
• Make build-vs-buy decisions for database technologies
• Significant experience as a software engineer building and operating production database or storage systems
• Deep knowledge of distributed database architectures and OLTP systems at scale
• Proficiency with SQL and at least one major relational or distributed database engine (e.g., PostgreSQL, MySQL, Spanner, CockroachDB, DynamoDB)
• Track record of leading large, complex infrastructure projects as an engineer or tech lead
• Ability to balance moving quickly with the reliability needs of production systems
• Strong technical leadership and cross-functional collaboration skills

Note: Prior AI/ML infrastructure experience is not required. We value deep infrastructure and database expertise from any domain.

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.

• 10+ years building and scaling database systems, with 3+ years leading large-scale projects or teams
• Experience scaling databases through periods of rapid growth at high-growth companies
• Experience operating Spanner, CockroachDB, TiDB, AlloyDB, or other globally distributed SQL databases in production
• Experience with Redis, Temporal, vector databases, or async job processing frameworks

$320,000—$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.

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.

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.