Staff Software Engineer
Anthropic
Staff Software Engineer
Anthropic
Builds Claude AI models with a focus on safety
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.
Anthropic exists to ensure the world safely navigates the transition through transformative AI. That work is funded by commercial revenue — and every dollar of it runs through Billing Platform. We build and operate the infrastructure that turns product usage into revenue across everything Anthropic ships: Claude.ai, the Developer Platform, Claude Code, and whatever comes next. The faster we can price it, charge for it, and account for it correctly, the faster Anthropic can fund the mission.
We’re looking for a software engineer to join Billing. Depending on where you land, you might be building the integration contracts product teams plug into so they can launch a paid SKU without becoming billing experts, automating the quote-to-cash lifecycle so enterprise deals don’t bottleneck on manual ops, or building the reconciliation and data foundations that keep every revenue number trustworthy at audit time. This is production-critical infrastructure where correctness is non-negotiable — a rounding error here is a revenue discrepancy somewhere else — and you’ll work closely with Finance, Product, Sales, and Accounting to build systems that scale with the business.
Design and ship billing capabilities end to end — pricing primitives, payment flows, contract and entitlement models, revenue data pipelines — depending on the surface area you own.
Build for correctness first. Billing data is financial data; you’ll develop the instincts for where idempotency, reconciliation, and audit trails matter and where they don’t.
Own the interfaces. Whether it’s the billing API a product team integrates against or the revenue dataset Finance closes the books on, you’ll design contracts that hide the complexity and hold up under change.
Make build-vs-buy calls. We lean heavily on third-party billing, payment, and tax platforms, and you’ll decide where to extend them and where to build our own primitives around them.
Own the payments stack. Authorization rates and retry logic so a good card doesn’t silently decline, processing cost as a real number you drive down, automated dispute response, and fraud controls that stop bad actors without blocking real customers.
Drive down the manual work. Enterprise contract amendments, pricing config changes, billing support escalations — a lot of it is still human-in-the-loop, and closing that gap is a direct line to scale.
Operate what you ship. You’ll own SLOs on customer-facing flows, instrument the revenue pipeline so discrepancies surface before month-end close, and be on the hook when it pages.
Partner across the company. Growth wants promotional mechanics, Sales wants quote flexibility, Finance wants GAAP-clean data, product teams want it yesterday — you’ll help thread that needle.
Have 8+ years building backend or platform systems in production, 3+ years leading large scale, complex projects or teams as an engineer or tech lead
Have a track record of shipping in fast-moving environments where the requirements shift under you and you still land something correct and maintainable.
Care about correctness and data integrity as first-class design concerns, not afterthoughts — and know how to build systems that are easy to reason about when money is on the line.
Enjoy cross-functional work. Billing sits between Product, Finance, Sales, and Legal, and a lot of the job is translating between those worlds.
Built billing, payments, subscription, or fintech systems before — and know firsthand how a small pricing change ripples through the whole stack.
Direct experience integrating or extending third-party billing and payment platforms, and opinions on where they fall short.
Worked on revenue reconciliation, financial reporting pipelines, or systems that had to survive an audit.
Experience with enterprise commerce — CPQ, quote-to-cash, contract management, or the operational side of B2B billing.
Owned payments optimization in a self-serve or PLG environment — authorization rates, payment cost, fraud, chargebacks — and know what it takes to move those numbers without breaking the good customers.
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.
For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
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.
Annual Salary: 405000 - 485000 USD
Anthropic builds the Claude family of AI models and sells them to businesses, software developers, and consumers, with research on making AI safe and understandable at the center of its work. In 2024 it introduced the Model Context Protocol, an open standard for connecting AI assistants to outside apps and data that OpenAI and Google adopted the next year. People use the Claude app to write and analyze files, programmers hand coding tasks to Claude Code, and companies build Claude into their own products through its API. Anthropic earns money from subscriptions, business plans, and usage-based API fees. Siblings Dario and Daniela Amodei founded Anthropic in 2021 with other former OpenAI employees, and it is based in San Francisco.
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