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Salary
$405k – $485k per year
Location
Hybrid (San Francisco, United States)
Seniority
Staff
Visa
No sponsorship (stated in the posting)

Confirmed on the employer's own hiring board on Oct 15, 2026. First seen by Alion on Oct 14, 2026. Anthropic scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Anthropic is an American artificial intelligence safety and research company founded in 2021 by former OpenAI researchers, among them the siblings Dario and Daniela Amodei. It develops the Claude family of large language models and ships them through a consumer assistant, an enterprise developer platform and the Claude Code agentic coding tool, alongside open standards such as the Model Context Protocol. Incorporated as a public benefit corporation and headquartered in San Francisco, the company concentrates on interpretability, alignment and reliability research and counts Google and Amazon among its largest investors.

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. Writing a change is fast now, and the hard part is knowing it's 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 backend and infrastructure background 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

  • Own the technical strategy and roadmap for your area, and make sure its hardest problems get solved, by you or through others
  • Stay hands-on: design, build, and operate the tools that help Platform teams ship code faster
  • Define what it takes to trust a change, including changes written by Claude, and build the tooling that holds that bar before and after merge
  • 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
  • Measure developer experience and adoption, and use the data to decide what to build next
  • Move between building new tools and improving the shared systems teams already depend on, as priorities shift

You might be a good fit if you:

  • Experience building and operating large-scale backend services or distributed systems in production
  • Proficiency in Go, Python, Rust, or TypeScript
  • Deep experience with developer tooling, CI/CD, test infrastructure, or deployment systems
  • Experience with cloud infrastructure and container orchestration
  • Experience leading large, complex technical projects across teams, from an ambiguous problem to a tool people use
  • 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
  • Depth in progressive delivery, observability, VM orchestration, sandboxed execution, or workflow orchestration
  • Experience working in a large monorepo
  • Enough full-stack ability to put a usable interface on your tools
  • 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 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.

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