Engineering Manager, Enterprise

Job Application for Engineering Manager, Enterprise at Anthropic

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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

Enterprise is central to Anthropic's mission. The organizations that could benefit most from Claude are often the most demanding buyers, with rigorous requirements around security, compliance, and control. We believe earning their trust is essential to ensuring AI benefits the world broadly.

We're looking for an engineering manager for our Enterprise pillar —the team that makes Claude enterprise-ready at scale. When a Fortune 500 company wants to roll out Claude to 100,000 employees, we're the team that makes it possible.

You'll build the foundational systems that large organizations require before they can deploy AI at scale. This work directly converts product-market fit into revenue by removing the deployment blockers that prevent large organizations from adopting Claude broadly.

This role sits at the intersection of enterprise product, platform infrastructure, and go-to-market. You'll partner closely with product, design, sales, and customer success to understand what our largest customers need, then translate those requirements into scalable technical solutions that work across Claude.ai , Claude Code, and API.

Responsibilities

Lead and develop a team of engineers building out features and foundations that make Claude enterprise-ready at scale

Own engineering execution end-to-end: planning, prioritization, delivery quality, team health, and incident response

Partner with engineering teams throughout the company to ensure that the platforms we build are extensible and easy to adopt

Partner with sales and customer success on enterprise deals—understanding requirements, representing engineering in key conversations, and turning what you learn into priorities

Shape the roadmap with product and design, not just execute against it

Drive the compliance and platform-readiness work your customers require, partnering with security and legal

Recruit, onboard, and grow strong engineers; give direct feedback and build a healthy, high-performing team

Minimum qualifications

4+ years of experience as an engineering manager, with experience building enterprise SaaS platforms or admin tools

Are comfortable executing at a fast pace to meet the expectations of our customers

Are detail-oriented and quality-focused - our customers are using Claude for critical workflows and our product needs to stay robust and reliable

Are comfortable working with enterprise customers, working alongside sales and customer success and joining customer conversations

Are a skilled engineering manager who treats management as a craft—clear feedback, strong 1:1s, consistent investment in your team's growth

Preferred qualifications

Experience with AI/ML products and understanding how enterprises evaluate and deploy AI tools

Background with compliance frameworks for regulated industries (SOC2, HIPAA) and enterprise audit logging requirements

Experience building integrations, permissions, billing, or pricing infrastructure

Familiarity with data residency and sovereignty requirements across global regions

Startup experience, particularly in scaling enterprise platforms from early adoption to broad deployment

Experience in working with research to improve domain specific model capabilities

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.

Annual Salary: $405,000 - $485,000 USD

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.

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...