Staff+ Software Engineer, Platform Acceleration

Anthropic · Engineering & Design - Product

支持签证Anthropic H-1B 获批 76 次 (FY2025)英国签证担保名单$405k–$485k/年San Francisco, CA | New York City, NY | Seattle, WA发布 2026-10-13
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Visa sponsorship:  We do sponsor visas!

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职位描述 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

As of May 2026, Claude authored more than 80% of the code we merge . In September 2026, we merged more than 30,000 changes per day . Writing a change is fast now, and the hard part is knowing what is correct and safe to ship. Platform Acceleration builds the internal tools that close that gap for Anthropic's product engineers, who own the Claude API, our SDKs, and the rest of the Claude Platform. We work like a small product team whose customers are other Anthropic engineers.

We're looking for Staff+ engineers with a strong background in backend or infrastructure who care about developer experience and have built tools other engineers rely on. We prefer candidates who can work from our San Francisco office, and we'll also consider candidates based in Seattle.

What you'll do

Design, build, and operate the tools that help product teams ship faster

Own the technical strategy and roadmap for your area, and make sure its hardest problems get solved, by you or through others

Define what it means to trust a change, especially changes written by Claude, and build the tooling that holds the bar throughout the software development lifecycle

Build agents that take on repetitive engineering work, such as diagnosing failures, fixing broken tests, and running migrations

Embed with partner teams to find their biggest sources of friction, validate a solution with them, and turn the fix into a product other teams can adopt

Move between building new tools and improving the shared systems that teams already depend on, as priorities shift

You might be a good fit if you:

Experience building and operating backend services or infrastructure in production, in Go, Python, Rust, or TypeScript

Deep experience with developer tooling, CI/CD, test infrastructure, or deployment systems

Experience leading large, complex technical projects across teams, from an ambiguous problem to a solution developers adopt

Clear written and verbal communication, with experience supporting internal partner teams

Interest in Anthropic's mission of building safe, beneficial AI

Preferred qualifications:

Experience at a startup or on a similarly small team, taking a product from zero to one and talking directly to your users

Substantial experience with agents that do engineering or other technical work

Experience building widely adopted CLI tools, developer-facing services, GitHub automation, or open source developer tools

Experience measuring developer productivity and using the data to decide what to build

A point of view on how software engineering changes as agents write more of the code

Deadline to apply:  None. Applications will be reviewed on a rolling basis.

Location Preference: Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of team.

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:

$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.

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 traditiona

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