GitLab

Backend Engineer, Create: Repository Management

Backend engineer building dependable server-side logic that lets customers configure repositories and rules, including safeguards for AI agents, within GitLab's Source Code stage.

The role

This engineer joins the repository management group inside GitLab's Source Code stage, which covers one of the platform's oldest and most intricate product areas. The work centers on giving customers control over how their projects are set up, with extra protections so automated agents operate safely alongside people.

What you would do

  • Build hardened, thoroughly verified, and quick features in Ruby and GraphQL.
  • Untangle intricate requirements and older architectural limits while keeping this key system dependable.
  • Create server-side services, API endpoints, data schemas, and rule logic that drive repository configuration.
  • Partner with peers in other groups, both live and asynchronously, pulling in specialists and asking for direction when stuck.
  • Apply AI agents to clearly bounded tasks where they add speed, and scrutinize their results.
  • Produce clean code that matches internal conventions and act on reviewer comments.
  • Support production stability by watching health indicators, joining the second-tier on-call rotation, investigating incidents, and improving monitoring and fault tolerance.
  • Pass along know-how through reviews, documentation, and daily teamwork while absorbing lessons from teammates.

What they asked for

  • Prior hands-on work constructing server-side web apps, services, or endpoints; Ruby and GraphQL experience preferred, or demonstrated ability to pick them up.
  • Working knowledge of relational data stores, query language, schema design, caching, asynchronous job processing, and backend speed optimization.
  • Exposure to permission or rule-driven features in web products and experience keeping that complexity manageable.
  • Ability to write server-side unit and integration tests; comfortable with Git and peer review workflows.
  • Hands-on use of AI coding assistants, with the judgment to verify output and recognize when to ask for help.
  • Solid written and spoken English for status reporting and productive remote, asynchronous work.
  • Ability to juggle priorities, handle uncertainty, own deliverables, and check in before making irreversible choices.
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