Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 6
API @ 3
ClickHouse
Data Engineering
Data Modeling @ 3
Go @ 3
Kafka @ 6
OLAP @ 6
Observability
Ruby @ 3
Rust @ 3
Security
Software Development @ 3
TypeScript @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
GitLab is hiring an Intermediate Backend Engineer for the GitLab Orbit team to help build and operate a graph data service supporting 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 builds a property graph from GitLab's software development lifecycle (SDLC) and code data. It uses ClickHouse, NATS JetStream, and the Data Insights Platform, and exposes secure graph queries and MCP tools used by AI agents and product features. The role involves delivering features in well-scoped areas while contributing to reliability, observability, and operational readiness.
Responsibilities
- Implement and iterate on backend features in the Rust-based Knowledge Graph service, including query engine changes, SDLC and code indexing flows, and API endpoints, including MCP endpoints.
- Maintain integrations with 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 related to reliability, scalability, and maintainability.
- Improve operational maturity through metrics, logging, runbooks, alerts, and service-readiness tasks.
- Participate in on-call rotation as appropriate for the level and experience of the role.
- Collaborate asynchronously with product, data, infrastructure, security, and AI teams in an all-remote environment.
- Use AI-assisted development workflows responsibly, validate outputs, and share effective practices 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 and authorization paths and small frontend changes related to Knowledge Graph features such as Software Architecture Map UI plumbing.
Requirements
- Professional experience building and maintaining backend systems in production, including understanding of reliability, maintainability, incident response, and follow-up work.
- Proficiency in at least one modern backend language and strong interest in Rust, with prior Rust experience or evidence of the ability to ramp up 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 (CDC) pipelines, or strong motivation to develop these skills.
- Interest in graph data modeling and query patterns, including property graphs, multi-step traversals, and aggregations.
- Practical experience or strong interest in using AI tools for day-to-day development, with a thoughtful approach to validating and integrating AI-generated output.
- Ability to learn new languages and frameworks as needed, such as Ruby, Go, or TypeScript/Vue.
- Solid system design fundamentals, including reasoning about trade-offs, asking effective questions, and aligning implementation work with architectural decisions.
- Comfort working in a low-process, high-ownership environment and communicating clearly in writing across time zones.
About the Team
GitLab Orbit is part of the Data Engineering organization and works with AI, analytics, infrastructure and delivery, and security teams. The team collaborates asynchronously and is focused on sustainably scaling usage, hardening multi-tenant behavior, and reducing operational single points of failure.
Benefits
- Benefits supporting health, finances, and well-being
- Flexible paid time off
- Team member resource groups
- Equity compensation and employee stock purchase plan
- Growth and development fund
- Parental leave