Senior Backend Engineer (Ruby), AI Engineering: AI Coding at GitLab

Role overview

GitLab’s AI Engineering organisation builds AI-powered capabilities into its DevSecOps platform. These Senior Backend Engineer roles work on Ruby backend systems that connect external agents, AI coding workflows and event-driven automation to GitLab.

Responsibilities

• Design, build and maintain secure, tested and performant Ruby backend integrations and services.
• Connect GitLab agents with external tools and providers such as Slack, Claude Code, Codex and other workflow systems.
• Build event and trigger capabilities that respond to pushes, issues, merge requests, CI/CD results, deployments and third-party events.
• Define APIs, permissions, contracts and architectural patterns for exposing AI functionality safely.
• Collaborate with product, UX, frontend and AI engineering teams to deliver end-to-end features.
• Improve observability, test coverage and production reliability, and participate in incident response when required.

Qualifications

• Strong professional experience building production Ruby on Rails backends and APIs.
• Experience integrating external systems, event-driven workflows, webhooks or tool-calling interfaces.
• Understanding of secure API design, permissions, testing, performance and backward compatibility.
• Ability to work across a large monolith and adjacent services while making pragmatic architectural decisions.
• Experience with AI-assisted or agentic software systems is valuable, as is familiarity with developer tools and CI/CD.
• Strong written communication and ability to collaborate in a remote, async-first team.

Technology in this role

• Python: • Additional helpful experience includes Python, since other parts of GitLab's AI platform are built in it, and using GitLab as a .
• Ruby on Rails: Strong professional experience building production Ruby on Rails backends and .
• Ruby: These Senior Backend Engineer roles work on Ruby backend systems that connect external agents, AI coding workflows and event-driven automation to .
• large language models: • Proven track record building products that interact with large language models, not training or building machine learning models yourself, but with hands-on experience integrating large language models into real, user-facing .
• Jenkins: The platform handles internal GitLab events like code pushes, issue and merge request changes, continuous integration and continuous delivery (CI/CD) pipeline results, and deployments, as well as custom events from third-party tools like Jira, Jenkins, and .
• CI/CD: Build event and trigger capabilities that respond to pushes, issues, merge requests, CI/CD results, deployments and third-party .
• CAN: Flow Triggers link projects to flows, firing automatically when matching events occur, so that AI-powered workflows like automated code review can run without anyone lifting a .
• Rails: Strong professional experience building production Ruby on Rails backends and .
• Jira: The platform handles internal GitLab events like code pushes, issue and merge request changes, continuous integration and continuous delivery (CI/CD) pipeline results, and deployments, as well as custom events from third-party tools like Jira, Jenkins, and .

Role-specific candidate guide

Preparation notes based on the employer’s stated responsibilities and qualifications.

Understanding the scope. This Senior Backend Engineer (Ruby), AI Engineering: AI Coding position at GitLab is best assessed through the work described in the employer’s posting, rather than the title alone. The available role overview says: “GitLab’s AI Engineering organisation builds AI-powered capabilities into its DevSecOps platform. These Senior Backend Engineer roles work on Ruby backend systems that connect external agents, AI coding workflows and…” Read that statement together with the responsibilities below to understand the likely balance between delivery, coordination and technical decision-making. The role belongs to the AI and data area, but that label is only a guide to the work; the employer’s own requirements remain decisive. Before applying, check the original listing for reporting lines, product or team assignment, employment terms and any details that may have changed since this copy was checked. Where this page says a fact is not specified, treat it as an open question rather than an implied promise.

What the responsibilities signal. The posting specifically names “Design, build and maintain secure, tested and performant Ruby backend integrations and services.”; “Connect GitLab agents with external tools and providers such as Slack, Claude Code, Codex and other workflow systems.”; “Build event and trigger capabilities that respond to pushes, issues, merge requests, CI/CD results, deployments and third-party events.”. For each duty, identify a project where you performed comparable work and be ready to describe the context, your own contribution, constraints, decisions, and measurable result. Explain how you moved from the initial need to implementation, review, release or operational follow-through, where those stages apply. If the work involved other teams or users, distinguish your decisions from the group’s contribution. Avoid presenting a technology keyword as proof by itself: connect it to the problem you solved, the scale or complexity involved, and what changed after your work. The source may contain additional duties; review it directly before preparing your application.

How to read the requirements. The listed qualifications include “Strong professional experience building production Ruby on Rails backends and APIs.”; “Experience integrating external systems, event-driven workflows, webhooks or tool-calling interfaces.”; “Understanding of secure API design, permissions, testing, performance and backward compatibility.”. Mark each requirement as demonstrated, adjacent experience or a genuine.

Benefits

• Equity Compensation & Employee Stock Purchase Plan

About GitLab

GitLab is a remote-first DevSecOps platform company. Its AI Engineering teams connect AI agents, coding workflows and lifecycle events to software delivery.

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