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
We're looking for an experienced engineering leader to build and lead our Enterprise Engineering team as a key part of our Claude for Work initiative. This leadership role requires deep expertise in developing enterprise software solutions with exceptional security, compliance, and scalability standards. You'll be responsible for building a high-performing engineering team focused on creating trustworthy AI experiences that meet the needs of business customers from small teams to large organizations.
As the EM for Enterprise, you'll work closely with product, design, sales, customer success, and professional services teams to deliver features that drive adoption and retention of Claude in corporate environments.
Responsibilities:
- Build and lead a high-performing team of engineers focused on enterprise software solutions
- Define and execute the technical strategy for enterprise initiatives, including architecture decisions, security frameworks, and compliance requirements
- Create clarity and direction for the team in a fast-moving, ambiguous environment
- Develop admin and governance features that enable enterprise-wide deployment and adoption
- Ensure enterprise compliance and security requirements are met across our business products
- Take an inclusive, equitable approach to hiring and coaching technical talent
- Drive the development of scalable systems for enterprise deployment, user management, and administrative controls
- Collaborate cross-functionally with product, design, sales, and customer success teams to identify and prioritize enterprise customer needs
You may be a good fit if you have:
- 5+ years of experience as a product-minded engineering manager, with at least 3 years leading enterprise software engineering teams
- Strong technical background in software development with proven success building and shipping enterprise-grade applications
- Experience with identity management, SSO integration, compliance frameworks (such as SCIM, SSO, FERPA, HIPAA), and enterprise security standards
- Track record of building systems that successfully scale from small business to enterprise customers
- Experience recruiting, scaling, and retaining engineering talent in a high-growth environment
- Excellent leadership and communication skills, with ability to work effectively across functions
- Demonstrated success in building a culture of engineering excellence
Strong candidates may also have experience with:
- Experience integrating and working with AI/ML models and understanding their capabilities
- Background in SaaS platforms with enterprise management features
- Experience with multi-tenant architecture and enterprise deployment models
- Startup experience, particularly in scaling products from zero to one
- Knowledge of enterprise billing systems and seat management
- Experience partnering with sales, customer success, and professional services teams to drive enterprise adoption
Deadline to apply: None. Applications will be reviewed on a rolling basis.
The expected salary range for this position is:
Annual Salary:
$405,000—$485,000 USD
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 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.
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.
