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.
Since launch, the Anthropic API has seen rapid growth and adoption by companies of all sizes to build AI applications with our industry-leading models. We're looking for an experienced engineering leader to lead our Claude Developer Product Experience team, who is responsible for creating a world-class developer experience for the Anthropic API. The team owns the end-to-end flow for using the Anthropic API, including everything from documentation and SDKs to prompt engineering and model customization tools.
EMs currently hiring:Developer ExperienceOur Developer Experience team strives to build best in class experiences for developers building on Claude APIs. This includes our SDKs, documentation, console experiences, and observability. As our platform continues to support more and more complex integrations, the Developer Experience team is obsessed with ensuring that developers have high quality tools to set them up for success.
Platform ToolsIncreasingly complex businesses are building integrations on top of the Claude Developer Platform. The Platform Tools team has a goal to spend time with these customers, learn what they need in order to build the integrations they need to build, and improve the platform to support these use cases.
Responsibilities:- Lead a team in crafting an industry-defining developer experience for building AI applications
- Collaborate with product and research teams to define the vision and developer roadmap
- Create clarity for the team and stakeholders in an ambiguous and evolving environment
- Work cross functionally to design clear interfaces and processes for shipping products that span many teams
- Take an inclusive, equitable approach to hiring and coaching top technical talent, and maintain a high performing team
- 5+ years of experience as an engineering manager
- A background in fullstack development - comfortable diving into various technology stacks frontend, backend, and at times deeper infrastructure.
- A strong product mindset, able to navigate through ambiguity, and willingness to wear multiple hats (e.g. product management, design)
- Experience recruiting, scaling, and retaining engineering talent in a high growth environment
- Excellent leadership and communication skills
- Demonstrated success in building a culture of belonging, and of product and engineering excellence
- Startup experience, building products from zero to one
- Experience building APIs and/or developer products for external developers
- Expertise in modern web development stacks (React, Next.js, etc)
- Experience working on AI/ML products
Deadline to apply: None. Applications will be reviewed on a rolling basis.
Location Preference: Preference will be given to candidates based in the SF and Seattle areas as this position is 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.
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 differentWe 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
Top Skills
What We Do
Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.
