Staff GTM Systems Engineer

CodeRabbit Inc.
San Francisco, CA, United States
30 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Compensation
$210,000 - $250,000
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Amazon Web Services Systems Engineering BigQuery Business Systems Code Review Databases Extract Transform Load (ETL) Data Warehousing Github Python (Programming Language) PostgreSQL
+14 more
Next.js Runbook Salesforce.Com TypeScript Web Applications Apex Code Google Cloud Large Language Models Claude Code Agentic-AI Build Management Stripe Marketplace Zuora

Job description

  • 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.

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., * 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.

Benefits & conditions

  • $210K - $250K, Target salary for this role is $210k-$250k, plus equity. Actual salary will be based on candidate skills, experience and location. Compensation Range: $210K - $250K

About the company

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.

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