Customer Success Programs Manager

Anthropic Anthropic · AI Frontier · New York, NY +1 · Sales

This role is for a Customer Success Programs Manager at Anthropic, focusing on building and scaling AI-native customer engagement programs using Claude. The role involves designing and shipping programmatic plays, leveraging AI agents and automated journeys to drive customer adoption and value realization. It requires a blend of customer success program expertise and hands-on experience with AI tools to create repeatable, self-serve solutions.

What you'd actually do

  1. Build and run a portfolio of programmatic CS plays **(activation, scale and expand) across the long tail and unmanaged segments, spanning Claude Enterprise; Cowork, and Claude Code.
  2. Design and ship Claude-powered engagement plays** that replace or augment traditional CSM touchpoints: use-case discovery chats, digital QBRs, health reviews, feature nudges, consumption-drop saves, and expansion prompts. Define entry criteria, agent behavior, exit criteria, and success metrics for each.
  3. Design and deliver high-leverage live engagements. 1:many webinar series, onboarding cohorts, customer communities, and academies, and look for every opportunity to make them AI-native, repeatable, and self-serve over time.
  4. Flex across the needs of the function. Some weeks the priority is an agent; some weeks it's a cohort or a community launch. You bring comprehensive knowledge of what effective CS programs look like and apply the right model to the problem in front of you.
  5. Instrument every program** with consumption, product telemetry, and qualitative signals. Know which touchpoints — digital or live — deliver the most value and where the handoff between digital and human should sit, and invest accordingly.

Skills

Required

  • 6-8+ years in Customer Success, with meaningful time in a Digital, Scaled, or Programmatic CS function.
  • A clear track record of delivering measurable customer outcomes; activation, adoption, NRR, retention, without a dedicated 1:1 relationship.
  • Shipped lifecycle programs, in-app flows, digital QBRs, academies, webinar series, community programs, or churn-save automations that moved real numbers.
  • Hands-on fluency with AI in your own workflow. You've prototyped agents, generated content, analyzed accounts, or replaced internal processes with LLMs and you can talk concretely about what worked, what didn't, and what's next. You don't wait for AI tooling to arrive; you build it.
  • Direct experience running live 1:many engagements. Webinar series, onboarding cohorts, communities, or academies and the instinct to make them more AI-native and repeatable every time you run them.
  • Comprehensive knowledge of effective CS programs and the range to flex across them. You know the strengths and failure modes of tech-touch, pooled, 1:many, and digital models, and you pick the right one for the problem rather than defaulting to the one you know best.
  • Strong data instincts. You're comfortable analyzing trends, reading consumption dashboards, and translating product telemetry into triggers.
  • Technical literacy with API-first and developer-facing products. You can follow a Claude Code workflow, reason about token economics, and have a credible product conversation with technical customers and PMs.
  • Excellent written communication. Most of your output is customer-facing copy, prompts, agent instructions, facilitation guides, and playbooks. Tone, clarity, and specific

Nice to have

  • SQL or lightweight scripting is a plus.

What the JD emphasized

  • AI-native lifecycle flow
  • build an agent or an automated journey
  • shipping an AI-native lifecycle flow
  • Claude-powered engagement plays
  • agent prompts
  • workflow logic
  • agent instructions