Backend Engineer, Knowledge Graph (Rust) - GitLab

About the Role

As an Intermediate Backend Engineer on the GitLab Orbit team, 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. You'll join a Rust-first team that values clear ownership, thoughtful system design, and rigorous thinking about data and reliability.

The Knowledge Graph service is a Rust backend that builds a property graph from GitLab’s software development lifecycle (SDLC) and code data. It uses ClickHouse, NATS JetStream, and the Data Insights Platform. It exposes secure graph queries and Model Context Protocol (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 with better tests and runbooks, and help the team ship analytical services that are easier to maintain and evolve over time.

What You'll Do

• 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 the GitLab Duo Agent Platform.
• Contribute to system design discussions by proposing options, raising questions, and documenting decisions, with a focus on reliability, scalability, and maintainability for analytical graph workloads.
• Improve the operational maturity of the service by adding or enhancing metrics, logging, runbooks, alerts, and participating in on-call rotation as appropriate for your level and experience.
• Collaborate asynchronously with product, data, infrastructure, security, and AI counterparts to clarify requirements, align on scope, and ship features safely and sustainably.
• Use AI-assisted development workflows responsibly (e.g., using Knowledge Graph-backed agents and internal Duo tooling) and share best practices while maintaining high code quality and correctness.
• Participate in code reviews, knowledge-sharing sessions, and pairing to maintain consistent standards across the codebase.
• Contribute across the stack when needed, including occasional Ruby work for Rails integration and authorization paths, or small frontend changes related to Knowledge Graph features.

What You'll Bring

• Professional experience building and maintaining backend systems in production, with an understanding of reliability, maintainability, and operational support (e.g., incident response).
• Proficiency in at least one modern backend language and a strong interest in Rust, with either prior Rust experience or clear evidence of ramping quickly in a Rust-first, performance-sensitive codebase.
• Exposure to distributed data or analytics systems (such as OLAP databases, Kafka- or NATS-style messaging, or change data capture pipelines), or strong motivation to develop these skills.
• Interest in graph data modeling and query patterns (property graphs, multi-step traversals, aggregations).
• Practical experience (or strong interest) using AI tools in day-to-day development with a thoughtful approach to validating outputs.
• A language-agnostic mindset and willingness to pick up adjacent languages and frameworks as needed (such as Ruby, Go, or TypeScript/Vue).
• Solid fundamentals in system design, including the ability to reason about trade-offs and align implementation with documented architectural decisions.
• Comfort working in a low-process, high-ownership, all-remote environment with strong written, asynchronous communication skills across time zones.

About the Team

GitLab Orbit sits within the Data Engineering organization, working closely with partners across AI (Duo Agent Platform), analytics, infrastructure and delivery, and security. We collaborate asynchronously rather than following a feature factory model, with an active focus on scaling sustainably and hardening multi-tenant behavior.