Software Engineer, Claude Developer Platform; Full Stack

Staff Software Engineer, Claude Developer Platform (Full Stack)

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:

Anthropic is looking for a product‑minded engineer to build a world‑class developer experience for the Anthropic API. You’ll build the tools to accelerate developers from idea to deployment. In particular, you'll help figure out how to leverage Claude to improve developer's usage of the API, such as generating and evaluating prompts. You’ll collaborate closely with other product teams to bring Claude's current and future capabilities to developers.

We have multiple roles open on this team and are looking for experienced engineers at different stages in their career who are excited about this space and our mission.

Responsibilities:

• Build out the frontend and backend for helping developers bring their applications to production

• Partner with partner teams to ensure new product features are integrated into the developer console in an intuitive way

• Use product sense to propose and implement improvements to the developer experience of using the API

• Work with researchers to understand new model capabilities and design unique products that help users maximize their use of the Anthropic API

You might be a good fit if you:

• Have 7‑10+ years building production full‑stack software with a focus on usability

• Have strong communication skills and user empathy to understand needs

• Are an expert in modern web development stacks (React, Next.js, etc)

• Have demonstrated a strong product mindset and a focus on iterative product development

• Have startup experience, building products from zero to one

• Have experience building APIs and/or developer products for external developers

Strong candidates may also:

• Have experience with React and frontend frameworks

• Have experience with REST APIs

Final date to receive applications:
None. Applications will be reviewed on a rolling basis.

Location Preference:
Preference will be given to candidates based in the SF or Bay Area as these positions are part of an SF‑based team.

The expected base compensation for this position is below. Our total compensation package for full‑time employees includes equity, benefits, and may include incentive compensation.

$320,000 - $405,000 USD

Logistics

Education requirements:

We require at least a Bachelor's degree in a related field or equivalent experience.

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.

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…