Staff+ Software Engineer, Caching at Anthropic

Seattle, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

23 Sep, 26

Salary

485000.0

Posted On

25 Jun, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Distributed Systems, Caching Architectures, Redis, Systems Programming, Cache Invalidation, CDC, Multi-cloud Deployment, Client Library Design, Observability, Technical Leadership, Infrastructure Scaling, Latency Optimization, Go, Rust, Java, Python

Industry

Research Services

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 We're looking for experienced engineers to build Anthropic's cache layer as a managed service from the ground up. The Caching team is part of the Databases organization and owns the systems that keep Anthropic's hottest paths fast and correct: a managed Redis fleet, client libraries used across the company, and CDC-driven cache invalidation that solves one of distributed systems' hardest problems the right way. This is a foundational role on a small team with outsized leverage. Every millisecond you take off a hot path is multiplied across every Claude request. You'll set the technical direction for caching at Anthropic, from the data plane to the developer experience, and you'll work closely with product and research teams to make caching something engineers get for free rather than something they have to think about. Key responsibilities Drive the technical direction for caching infrastructure used across Product and Research Design, build, and operate a managed Redis fleet that scales to support millions of users across Claude's product ecosystem Build client libraries and developer-facing abstractions that make correct caching the default for Anthropic engineers Design and operate CDC-driven cache invalidation that keeps cached data consistent with source-of-truth databases Architect caching solutions that operate across GCP, AWS, first-party deployments, and other environments Optimize latency, hit rates, reliability, and cost efficiency on Anthropic's hottest paths Build observability and tooling that makes cache behavior easy to understand and debug Partner with product and research teams to understand access patterns and build infrastructure that accelerates their work Make build-vs-buy decisions for caching technologies Minimum qualifications Significant experience as a software engineer building and operating production distributed systems Deep knowledge of caching architectures, including invalidation strategies, consistency tradeoffs, and failure modes Experience operating Redis, Memcached, or similar in-memory data stores in production Proficiency in at least one systems programming language (e.g., Go, Rust, Java, C++) or Python at scale 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 Preferred qualifications 10+ years building and scaling distributed infrastructure, with 3+ years leading large-scale projects or teams Experience building managed infrastructure platforms or internal services consumed by many engineering teams Experience with change data capture (Debezium or similar) or streaming data infrastructure Experience operating Redis Cluster, Valkey, ElastiCache, Memorystore, or similar managed offerings at scale Experience designing client libraries or SDKs for internal infrastructure Experience scaling infrastructure through periods of rapid growth at high-growth companies Experience with multi-cloud or hybrid cloud deployments Contributions to caching systems, database internals, or related open source projects Note: Prior AI/ML infrastructure experience is not required. We value deep infrastructure expertise from any domain. 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. Annual Salary: $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. 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.

Responsibilities

Lead the technical direction and implementation of Anthropic's managed caching layer and Redis fleet. Design CDC-driven cache invalidation and developer-facing abstractions to optimize latency and reliability across the product ecosystem.