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Salary: USD 115,200 - 162,000 / annual
GitLab is seeking an Intermediate Backend Engineer to join the Orbit team within Data Engineering. You'll help build and operate a graph data service that supports GitLab Duo agents, analytics, and architecture-level features across GitLab.com, Dedicated, and Self-Managed deployments.
The Knowledge Graph service is a Rust backend that constructs a property graph from GitLab's software development lifecycle (SDLC) and code data. It leverages ClickHouse, NATS JetStream, and the Data Insights Platform to expose secure graph queries and MCP tools used by AI agents and product features. In this role, you'll deliver features and improvements in well-scoped areas, learn the broader architecture, and contribute to reliability, observability, and operational readiness.
In your first year, you'll take clear ownership of specific components or features—such as parts of the SDLC indexing pipeline or query paths. You'll help reduce single points of failure through better tests and runbooks, and contribute to shipping analytical services that are easier to maintain and evolve.
Key responsibilities include:
- Implement and iterate on backend features in the Rust-based Knowledge Graph service, including changes to the query engine, SDLC and code indexing flows, and API endpoints (including MCP endpoints) under guidance from senior and staff engineers
- Maintain integrations between Knowledge Graph and the rest of the GitLab platform, working across GitLab Rails, the Data Insights Platform (Siphon, NATS, ClickHouse), and GitLab Duo Agent Platform
- Contribute to system design discussions by proposing options, raising questions, and documenting decisions with focus on reliability, scalability, and maintainability
- Improve operational maturity by adding or enhancing metrics, logging, runbooks, alerts, and readiness tasks; participate in on-call rotation as appropriate
- Collaborate asynchronously with product, data, infrastructure, security, and AI counterparts to clarify requirements and ship features safely
- Use AI-assisted development workflows responsibly and share learnings with the team
- Participate in code reviews, knowledge-sharing sessions, and pairing
- Contribute across the stack when needed, including occasional Ruby work for Rails integration or small frontend changes
The team works within a low-process, high-ownership environment with asynchronous collaboration across time zones. Current challenges include scaling sustainably as usage grows and hardening multi-tenant behavior.
REQUIREMENTS:
- Professional experience building and maintaining backend systems in production, with understanding of reliability, maintainability, and service support over time (incident response and follow-ups)
- Proficiency in at least one modern backend language and strong interest in Rust; either prior Rust experience or clear evidence of ability to ramp quickly and deliver in a Rust-first, performance-sensitive codebase
- Some exposure to distributed data or analytics systems (OLAP databases, Kafka- or NATS-style messaging, CDC pipelines) or strong motivation to develop those skills in this role
- Interest in graph data modeling and query patterns (property graphs, multi-step traversals, aggregations) and willingness to learn Knowledge Graph tools and concepts
- Practical experience or strong interest using AI tools in day-to-day development, with thoughtful approach to validating outputs
- Language-agnostic mindset with evidence of ability to pick up new languages and frameworks (Ruby, Go, TypeScript/Vue)
- Solid fundamentals in system design for your level, including ability to reason about trade-offs and align implementation with architectural decisions
- Comfort working in low-process, high-ownership environment with responsibility for work, problem refinement with teammates, and clear written communication across time zones
