Staff Backend Engineer

About the Role

Guide the technical direction for GitLab's self-managed deployment strategy, enabling customers to deploy, upgrade, and run GitLab reliably in their own infrastructure with minimal disruption.

Responsibilities

• Guide the technical vision and architecture for GitLab’s cloud-native, self-managed deployments and upgrade workflows.
• Design and maintain Kubernetes Operators, Helm charts, and upgrade orchestration tooling for self-managed GitLab deployments.
• Develop automation and integration frameworks for database migrations, rolling deployments, and rollback paths.
• Drive observability, testing, performance, and resilience practices for self-managed deployments.
• Mentor engineers and enable customer-facing teams through design reviews, code reviews, and documentation.

Requirements

• Strong software engineering experience designing and delivering production systems that customers install and operate in their own infrastructure.
• Proficiency in Go for large, complex codebases.
• Hands-on experience with Kubernetes in production, including building and maintaining Operators and designing Helm charts for stateful applications.
• Knowledge of cloud-native systems and tooling, such as service mesh, observability stacks, and infrastructure as code.
• Experience with stateful workloads and databases, including PostgreSQL schema design and migrations.
• Understanding of Linux systems and production operations.
• Ability to guide through influence, including writing clear technical proposals and working effectively across teams.

Nice-to-Haves

• Familiarity with Ruby on Rails and Rails application architecture.
• Interest in open source infrastructure or deployment tooling.

About the Team

The Delivery - Operate team focuses on delivering GitLab to self-managed users through supported, validated deployment tooling. We own and evolve the GitLab Omnibus package, Helm charts, GitLab Operator, and the GitLab Environment Toolkit, enabling zero-downtime upgrades and reducing operational complexity at scale.