Pooled Customer Success Manager

Code Rabbit is the leading AI code review platform, trusted by more than 17,000 customers and 150,000 open-source projects, conducting over 2 million code reviews each week. We build the symbiotic partnership between developers and AI that makes shipping fast software safe again, reviewing every pull request, IDE change, and CLI commit so teams can move quickly without breaking things.

We are a fast-moving, well-funded company, fresh off a $143M Series C at a $1.5B valuation — building Agentic Change Management, the control layer for software changes created by humans and agents. As AI writes more of the world's code, the bottleneck moves from implementation to judgment and helping human judgment scale is exactly the problem we exist to solve.

Code Rabbit 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, and works alongside a program manager, a content and enablement specialist and a success analytics engineer.

The pooled customer success team is new within it, and this is one of its first roles.

You work a shared queue of customer accounts. Work arrives 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. You pick the case up, find out what is going on, get the customer configured and back to work, and close it out with a record the next person can read.

What you learn from the customers you work with feeds the playbooks, the automated campaigns and the triggers themselves. You work with the pooled team, the Content and Enablement Specialist, and the account executive who works expansion in the scaled lanes.

Few customer success teams run this way yet. You will learn how to move an account from default settings to a configured, renewing customer in a handful of conversations, and how to tell from the data which accounts need a person at all.

• The queue: pick up triggered accounts, respond within the team's standard, and resolve or route each one

• Configuration: take customers from default settings to a setup that fits their repositories, including Path Instructions, Learnings, pre-merge checks, IDE and CLI, and MCP

• Saves: work cancellation and non-renewal signals, understand the reason, fix what can be fixed, and record what cannot

• Renewals: run the renewal conversation where the signals say one is needed

• The expansion hand-off: when you see seat headroom or a buying signal, qualify it and pass it to the account executive with the context they need

• Playbook feedback: every case the playbook did not cover becomes a note, and patterns across those notes become new content, a new trigger, or new automation

• Case records: notes clean enough that anyone on the queue can pick up where you left off

• Complete product onboarding and work your first cases alongside the team

• Work the queue at the team's response standard

• Document the first ten cases where the playbook was missing or wrong, and propose the fix for each

• Contribute to the team's first readout: cases by trigger, resolution, and configuration movement on the accounts you touched

• 2+ years in customer success, technical support or solutions for a developer-facing product

• You have worked a ticket queue or a shared inbox at volume and kept quality up

• You write clearly in tickets, email and documentation

• You want to know why a customer left, and you record it every time

• You are comfortable on a team where the playbook is still being written

• You can read a YAML configuration file, open a pull request, run a CLI, and talk to an engineer about their workflow without a script

• You have used Code Rabbit or another AI code review tool

• Working knowledge of CI/CD pipelines and Git Hub or Git Lab workflows

• Experience with Pylon, Customer.io or a similar success or support platform

• Familiar with AI tooling and examples of you using it in similar roles

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.