Job Closed
This listing is no longer active.
GitLab, founded in 2011 and based in San Francisco, California, maintains a distributed team of professionals that work remotely across multiple continents. GitLab advocates for pr
Staff Backend Engineer, Knowledge Graph – Rust
Location
India
Posted
68 days ago
Salary
0
Seniority
Lead
Job Description
Staff Backend Engineer, Knowledge Graph – Rust
GitLab
• Lead the design and evolution of core Knowledge Graph services in a production Rust codebase, including the graph query engine, SDLC and code indexing pipelines, and API/MCP surfaces that other GitLab teams and AI agents rely on. • Own complex, cross-cutting initiatives that span GitLab Rails, the Data Insights Platform (Siphon, NATS, ClickHouse), and GitLab Duo Agent Platform, from technical direction and design docs through implementation, rollout, and iteration. • Drive system design decisions that improve reliability, scalability, and maintainability for analytical (OLAP‑style) graph workloads. This includes multi‑hop traversals, aggregations, and multi‑tenant isolation. Document trade‑offs so the broader team can move quickly and stay aligned. • Define and improve operational maturity for the service, including service level objectives (SLOs), observability, runbooks, incident response, capacity planning, and production readiness (PREP) for GitLab.com, Dedicated, and Self-Managed deployments. • Collaborate asynchronously with product, data, infrastructure, security, and AI teams to sequence work, unblock platform‑level dependencies, and land features in a way that is safe for customers and sustainable for the team. • Apply AI‑assisted development workflows responsibly (for example, using MCP‑aware tools, Knowledge Graph-backed agents, and internal Duo tooling) and help establish practical norms for how the team uses AI while maintaining strong engineering judgment. • Mentor and support other engineers through pairing, technical design reviews, and knowledge-sharing, reinforcing shared ownership of the system and its operational sustainability. • Contribute across the stack when needed, including occasional Ruby (Rails integration and authorization paths) or frontend work (for example, the Software Architecture Map UI) to close gaps and keep delivery moving.
Job Requirements
- Significant experience building and operating production backend systems, with a track record of owning reliability, maintainability, and on-call readiness for services that support other product teams or platforms.
- Strong engineering skills in Rust or clear evidence you can ramp quickly and deliver in a Rust-first, performance-sensitive backend codebase.
- Strong system design skills, including making and explaining clear architectural decisions, documenting constraints, and aligning trade-offs with product and platform needs.
- Strong fundamentals in preparing and structuring information for AI agents: how to curate and organize what the agent sees, design systems that support effective LLM-powered behavior, and manage context windows and token usage.
- Comfort working in ambiguous environments, with the ability to work autonomously and stay self-directed. Demonstrated ability to identify problems, drive solutions, and take ownership.
- Experience with distributed data or analytics systems (for example, OLAP databases like ClickHouse or columnar stores, Kafka‑ or NATS‑style messaging, or change data capture (CDC) pipelines), and comfort reasoning about trade‑offs in that space.
- Familiarity with graph data modeling and/or query patterns (property graphs, Cypher/GQL, n-hop traversals, aggregations), or strong interest in developing that expertise in this role.
- Practical experience using AI tools in day-to-day development, with the ability to explain how you structure prompts, validate outputs, and fold AI assistance into a disciplined engineering workflow.
- A language-agnostic mindset and evidence that you can learn new languages and frameworks as the problem requires (for example, Ruby, Go, or TypeScript/Vue in adjacent parts of the stack).
- Excellent written communication and comfort collaborating asynchronously across teams and time zones in an all-remote environment.
- Interest in helping grow others through mentoring, thoughtful code review, and sharing context as the team scales and more customers adopt Knowledge Graph.
Benefits
- Benefits to support your health, finances, and well-being
- Flexible Paid Time Off
- Team Member Resource Groups
- Equity Compensation & Employee Stock Purchase Plan
- Growth and Development Fund
- Parental leave
- Home office support
Related Guides
Related Job Pages
More Backend Engineer Jobs
Associate Technical Architect – Databricks
QuantiphiPioneering AI-first solutions, solving complex business challenges through expertise, cloud, data engineering, and AI.
• As an associate Technical Architect at Quantiphi, you will solve big data problems and will develop solutions for migration, storage, and processing.
Senior .NET Developer – Financial Sector
DBDesign and Build The Future | Somos uma empresa Randoncorp
• Work on the development, maintenance and evolution of backend solutions with a focus on distributed architecture and high availability • Develop and maintain APIs using .NET and GraphQL, ensuring performance, scalability and security • Build and support solutions based on a microservices architecture, promoting decoupling and efficiency between components • Perform integrations between internal financial systems and platforms in a Banking-as-a-Service (BaaS) context • Implement tasks from technical backlog stories, ensuring a complete understanding of requirements before execution • Actively participate in technical refinements, contributing critical analysis, technical feasibility assessments and defining the best implementation approach • Challenge requirements and identify possible gaps, inconsistencies or improvement opportunities before development • Propose technical solutions and architectural evolutions based on backend development and system integration best practices • Collaborate with technical teams on the continuous evolution of product, architecture and internal processes • Take ownership of deliverables, demonstrating technical accountability and a clear focus on business impact.
• Desenvolvimento de software embarcado utilizando linguagem C e C++ • Desenvolvimento de testes automáticos para garantia da qualidade dos produtos • Participação em projetos da área
• Designing systems that allow AI to participate directly in developer workflows • Building infrastructure that connects language models with the editor and developer tools • Developing context systems that help models reason about large codebases • Designing evaluation frameworks for AI-assisted development • Improving the reliability, latency, and cost efficiency of AI features • Working closely with editor and infrastructure engineers to ship ideas quickly • Pair programming with teammates to explore ideas and refine systems together
