Staff GTM Systems Engineer

CodeRabbit•San Francisco, CA

5d•$210,000 - $250,000

About The Position

CodeRabbit 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. At CodeRabbit, our agents already write, review, and ship our Salesforce and internal tooling code. A Linear label or Slack emoji starts a pipeline: an agent plans the change, a human approves, the agent builds and tests it in a sandbox and opens a pull request, a second model reviews it, and guard hooks stop anything that could hurt production. This is our GTM Systems harness. We're looking for a Staff GTM Systems Engineer to own it and to architect the systems it builds: the pipeline generation, quote-to-cash, provisioning, and billing integrations behind a company growing from PLG into enterprise sales, and the internal tools our GTM teams run on. You'll be the senior technical voice in Business Systems, setting the patterns that engineers, analysts and agents all follow.

Requirements

Deep, hands-on Salesforce engineering: Apex, LWC, data modeling, sharing and security, and source-driven deployment with the Salesforce CLI.
Strong full-stack software engineering beyond Salesforce, with production web apps, APIs and databases you have built and run.
Real experience building with agentic coding tools such as Claude Code or Codex, including the guardrails that make agent output safe to ship: tests, CI gates, review, and scoped permissions.
A track record integrating GTM systems end to end, such as CRM to billing, CPQ, provisioning, the data warehouse and reverse ETL, pipeline generation workflows.
Staff-level judgment: you have owned architecture across systems you did not build, made decisions with teams that do not report to you, and changed how a team works.
Clear writing. Your design docs, PR descriptions and runbooks let others act without a meeting.

Nice To Haves

At least 7+ years of Salesforce and full-stack engineering.
Production experience with Python, TypeScript and Next.js.
Experience with Chargebee, Stripe, Zuora or another subscription billing platform, including usage-based or marketplace billing (AWS, GCP, GitHub Marketplace).
Experience building MCP servers, LLM evaluations, or human-in-the-loop approval workflows for agents.
Experience with BigQuery, dbt, Clay, or event-driven integration patterns.
Familiarity with developer-tools or technical B2B SaaS go-to-market, including a PLG to sales-led transition.

Responsibilities

Own and evolve the agentic engineering harness: the Agent Build pipeline, guard hooks, worktree tooling, CI, model routing and the permission tiers that keep agents safe around production.
Design and build internal tools and agents as full-stack applications (TypeScript, Next.js, Postgres, MCP servers) where off-the-shelf software falls short.
Build in Salesforce at a deep level: Apex service and selector patterns, triggers, LWC, Platform Events, permission sets and the metadata deployment model.
Set the engineering standards for Business Systems: architecture reviews, code review, testing, release and production runbooks, and how agent-written work gets reviewed and shipped.
Give the analysts and engineers on the team the platform to build their own agents, such as the Sales OS Agent and Data Quality Agent.
Partner with Finance, GTM, Deal Desk, and the Data teams to turn ambiguous business needs into systems that hold up at the next stage of scale.
Raise the technical bar across the team through pairing, reviews and design docs, and reduce our dependence on outside consultants over time.