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CodeRabbit

Regional Director of Pooled Customer Success

San Francisco, California, United States

Location
San Francisco, California, United States
Work
Hybrid
Employment
Full-time
Level
Director
Function
Customer success & support
Pay
$200K – $225K a year
Posted
4 weeks ago

About the role

About CodeRabbit

CodeRabbit is the governance and control layer for agentic software development, helping engineering teams trust the code they ship. AI can generate code faster than people can review and understand it. Teams still need to know whether each change solves the right problem, fits their architecture, and is safe to ship.

We provide independent validation grounded in codebase context and team standards, giving people the evidence they need to judge what should ship. Across Review, Triage, Explain, and Secure, our platform challenges changes before merge, prioritizes pull requests by value, impact, and risk, explains what changed and why it matters, and monitors the codebase for security vulnerabilities after merge.

CodeRabbit serves nearly 20,000 customers and supports approximately 300,000 open-source repositories, performing over 2 million code reviews each week. Our $143M Series C, raised at a $1.5B valuation, supports further product development and international expansion.

Location: San Francisco, Hybrid

About the team

CodeRabbit is the AI code review platform. Development teams install it on their repositories and it reviews every pull request, so it sits in the daily workflow of a large and fast-growing customer base. The Scaled Success team is responsible for the health of that base. It is a team of a program manager, a content and enablement specialist, a success analytics engineer and a success operations manager, reporting to the Director of Scaled Success. The pooled customer success team is the next team to be added, and this role leads it.

The role

You build and run the pooled customer success team. Work arrives on a shared queue when a signal fires: onboarding has stalled, nothing has been configured, the only active user has gone quiet, a renewal is approaching, a cancellation has been started, or a team is using fewer seats than it has bought. The signals come from our configuration maturity model, which scores every account on how deeply it has set up the product, and from the automated campaigns that escalate when a customer needs a person.

You design the queue, write the routing rules, set the response standards, build the playbooks, hire the team, and measure whether the motion holds retention in the band it covers. You work directly with the Director, the Scaled Success program manager, the Success Analytics Engineer and the Content and Enablement Specialist.

This team runs on signals, and the help arrives when the customer needs it. The person who builds it will learn how to run customer success this way from the inside, and will have the data to show what works.

What you'll own

  • Hiring and managing the pooled customer success managers, starting with the first hires in your first quarter
  • Queue design: which signals create work, how work is prioritized, the response and resolution standards, and how a case closes
  • The routing rules between the digital, pooled and named lanes, including the escalation path out of digital and the hand-back when an account grows into named coverage
  • The playbook library, one per trigger: what a CSM does on a dormant account, a solo user, a stalled onboarding, a cancellation notice, an approaching renewal. Written with the Content and Enablement Specialist and kept current from what the queue teaches you
  • The save lane: cancellation and non-renewal signals routed to a person, the reason captured on every one, and the fixable ones fixed
  • The expansion hand-off: when the team surfaces seat headroom or a buying signal, the account goes to the account executive working the scaled lanes, with the context they need to close
  • The team's readout: queue volume by trigger, time to first response, time to resolution, configuration movement, and retention of covered accounts, built with the Success Analytics Engineer and read monthly
  • Capacity: how many accounts one person on the queue can carry, measured from the queue, and the case for extending pooled coverage further down the base as triggers and playbooks mature

Your first quarter

  • Hire the first pooled customer success managers
  • Define the trigger set, the response standard for each trigger, and get the queue live in our tooling
  • Ship the first playbooks for the highest-volume triggers
  • Stand up the readout: queue volume by trigger, response and resolution times, and retention of covered accounts, reported on the team's measurement cadence

What you'll bring

  • 5+ years in customer success or technical support for a developer-facing product, with 2+ years managing people
  • You have built or run a shared-queue motion before: scaled success, a support desk, or a success pool where the team shared the work
  • You are technical enough for a code review product. You have shipped code, run CI, or supported developers doing both, and you can read a configuration file
  • You work from data. You can read a dashboard, question a number that looks wrong, and write a basic SQL query or specify the one you need
  • You have written operating procedures that other people followed
  • You are comfortable building where the playbook does not exist yet, and you document as you go

Nice to have

  • Experience with health scoring or trigger-based outreach in a success or support platform
  • Familiarity with Pylon, Customer.io, PostHog, Salesforce or their equivalents
  • Familiar with AI tooling and examples of you using it in similar roles
  • You have used CodeRabbit or another AI code review tool on your own repositories

How we work

The team runs on measured results. Campaigns ship with control groups, numbers are labeled by source, and every report traces to rules anyone can audit.

Source

Posted by CodeRabbit on their own hiring page, jobs.ashbyhq.com. OptiTalent shows it as published, read 07 Nov 2026 02:24 UTC; the original is the reference.

View the original ad ↗

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