Head of Programmatic Customer Success

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.

Anthropic's Customer Success organization covers our most strategic enterprise accounts through dedicated CSMs — but the majority of our customers will never be reached that way. Programmatic CS is how we close that gap: scalable digital journeys, AI-built engagement plays, and partner-delivered activation motions that drive habitual Claude adoption across a much broader customer base.

This is a new function, and you'd be its first leader. You'll report to the Head of Customer Success and work closely with Product, Partnerships, Growth Marketing, and Strategy to design and operate the system that moves customers from signed contract to deeply embedded usage — without a 1:1 CSM relationship to lean on.

The right person for this role has built something like this before, at real scale, and is genuinely excited to build it again from the ground up with better tools — including Claude itself as a core part of how the team operates.

Key responsibilities

Minimum qualifications

• Define and own the programmatic CS strategy: how we tier accounts, what motion each tier receives, and how customers move between them as their needs evolve
• Design and ship digital success programs — lifecycle communications, in-product nudges, self-serve onboarding — that drive activation and habitual usage without human-touch coverage
• Build and run AI-powered engagement plays that extend the team's reach; work with Product to clarify what this team builds versus what lives in the product itself
• Set the quality bar and requirements for partner-led activation, and maintain a tight feedback loop with our Partnerships team who owns the partner ecosystem
• Establish the metrics framework for programmatic success: define what "activated" means at each tier, identify leading indicators, and build the instrumentation to track them
• Run a rigorous experimentation program to understand which motions actually change customer behavior — and update the playbook when the data says to
• Hire and lead a small, high-leverage team; bring cross-functional partners along on the vision and the operating model
• Proven experience leading and building programmatic, digital success, lifecycle, or PLG motions at significant scale — with direct ownership of an adoption or activation outcome
• Track record of building scalable systems and programs, not just managing existing ones; you've started from a blank page before
• Strong cross-functional instincts — comfortable writing briefs that other teams execute against, resolving handoff ambiguity, and influencing roadmaps without direct authority
• Data-driven approach to decision-making, including experience designing experiments that distinguish real behavior change from activity metrics
• Experience managing and developing teams

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.

• Experience spanning more than one of: digital/PLG, partner ecosystems, lifecycle marketing, or scaled CS — ideally combined into a single integrated motion
• Hands-on familiarity with AI-powered workflows or automation as a force multiplier for a small team
• Background working at a fast-growing technology company where the playbook was still being written
• Experience with tiered coverage models and designing the handoffs between high-touch and low-touch

$315,000—$350,000 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.