Über diese Staff Software Engineer, Internal Products Stelle bei Anthropic
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
Our sales team is selling an increasing number of Anthropic products, at an ever-increasing volume. We are building the internal products our sellers and the teams who support them work in every day: how sellers manage their book, how deals get priced and approved, how renewals come together, and how a closed deal is handed off cleanly for billing and provisioning. Claude is our sellers’ personal assistant: Claude should do as much of the admin work as it safely can, and our sellers decide what needs a human.
We’re looking for Staff+ full-stack engineers to drive this work. You’ll build across the stack: the products sellers use and the agents that work alongside them. You’ll work directly with sellers, deal desk, finance and legal. A pricing error becomes a billing error, so correctness matters as much as speed.
This is a greenfield opportunity: you’ll shape the underlying systems, ship agents that help sellers organize their work, and design how agents and sellers get the right context to make high-quality deals, all from the ground up.
Key responsibilities
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Design and ship internal products end to end, from the data model to the UI, covering how sellers plan their day, how deals get approved, how renewals come together and how a closed deal is handed off to billing and provisioning.
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Put Claude to work on real selling tasks, such as preparing renewals, pulling together the context a deal needs or keeping account details up to date across the systems we already use, and decide where an agent should act and where a well-designed UI is the better answer.
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Make agents safe to trust with a deal: scoped access to customer and deal data, guardrails, evals, audit trails, and clear points where a person confirms before anything happens.
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Build one set of shared capabilities (such as pricing a deal, requesting an approval or handing off a closed deal) that people and agents both use, exposed as APIs and MCP tools, so the same rules and approvals apply to whoever makes the call.
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Treat speed and polish as product requirements. Spend time with sellers and the teams who support them, find where deals slow down, and remove those steps.
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Build for correctness. Downstream, a deal becomes revenue, a bill and a live account, so you’ll know where idempotency, reconciliation and audit trails matter and where they don’t.
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Integrate with the third-party systems sellers and the teams who support them already rely on, and build the layer on top of them where people and agents get their work done.
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Set technical direction for a domain over multiple quarters, lead engineers across teams through large, ambiguous projects, and raise the bar for the engineers around you.
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Operate what you ship: own the reliability of the workflows sellers depend on and be on call for them.
Minimum qualifications
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Production experience as a backend-leaning full-stack engineer, comfortable designing a data model, an API and the UI on top of them.
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Experience building software on LLMs or agents, and a point of view on when an agent should act on its own and when it should ask first.
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Experience leading the design and delivery of complex, user-facing products across the full stack, through requirements that shifted while you built.
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Experience designing for correctness and data integrity from the start, and building systems that are easy to reason about when money is involved.
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Experience working across functions, translating between sales, finance, legal and engineering to reach a decision.
Preferred qualifications
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Experience building internal products or workflow tools for sellers or the teams who support them. A plus, not a requirement; strong product generalists are just as welcome.
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Experience taking an agent into production for a high-stakes workflow, including the evals and guardrails that made it safe to ship.
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Experience building a zero-to-one product, or rebuilding one that people already depended on every day.
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Experience building pricing, billing or payments systems, and an understanding of how a small pricing change ripples through the stack.
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.
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.
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.
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.
