Manager, Account Executive - Enterprise Sales

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2 Locations
In-Office
360K-550K Annually
Artificial Intelligence • Natural Language Processing • Generative AI
The Role
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

As a Sales Manager at Anthropic, you'll lead a team of Enterprise Account Executives driving the adoption of safe, frontier AI by securing strategic deals with top enterprises in the Industrials, Retail, Telco, Media, and Business Services verticals. You'll leverage your leadership and consultative sales expertise to propel revenue growth while developing a high-performing team of AEs. Working closely with Applied AI Engineering and Product teams, you'll help customers embed and deploy AI while uncovering its full range of capabilities. In collaboration with GTM and Marketing teams, you'll continuously refine our value proposition, sales methodology, and market positioning to ensure differentiated value across the landscape.

The ideal candidate will have a passion for developing people, identifying market opportunities, and executing strategies to capture them. By leading the deployment of Anthropic's emerging products, you will help enterprises obtain new capabilities while also advancing the ethical development of AI.

Responsibilities:
  • Build and lead a high-performing team of Enterprise AEs - coaching, mentoring, and developing reps to consistently exceed revenue targets
  • Define and execute sales strategies, including territory planning, pipeline management, and accurate forecasting with strong CRM discipline
  • Partner with Applied AI Engineering to ensure your team can lead credible technical conversations and deliver optimized solutions pre- and post-sale
  • Collaborate cross-functionally with Enablement, Product, and GTM leadership to accelerate AE ramp, refine sales playbooks, and inform product direction through customer feedback
  • Identify and pursue new market opportunities and use cases for Anthropic's AI solutions, expanding the team's footprint within the vertical
You may be a good fit if you have:
  • 10+ years in enterprise sales with 5+ in leadership, including 3+ years leading teams selling into F1000 accounts; experience closing 7-figure deals

  • Proven track record building and scaling high-performing AE teams - coaching, developing reps, and establishing sales processes and methodologies in fast-growth environments

  • Strong technical acumen with the ability to understand complex AI solutions and enable teams to lead credible technical conversations alongside engineering partners

  • Operational rigor in pipeline management, forecasting, and navigating complex enterprise sales cycles with multiple stakeholders

  • Passion for AI technology and its safe, responsible development, with a strategic eye for new market opportunities and tactical excellence in execution

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:
$360,000$550,000 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 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

Anthropic Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Anthropic and has not been reviewed or approved by Anthropic.

  • Strong & Reliable Incentives Pay is positioned as top-of-market for many technical roles through a mix of high base pay, equity, and occasional bonuses/signing incentives. Benefits like substantial monthly stipends and employer-paid protections further strengthen perceived total rewards.
  • Healthcare Strength Healthcare is described as comprehensive across medical, dental, and vision, with additional mental-health support. Coverage is framed as robust for employees and dependents, which can materially increase the value of the overall package.
  • Parental & Family Support Paid parental leave is described as notably generous, alongside fertility coverage and other family-oriented supports. These elements broaden the rewards package beyond cash compensation and can improve retention for caregivers.

Anthropic Insights

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The Company
HQ: San Francisco, California
2,500 Employees

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.

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