Intermediate Backend Engineer - Code Security

Intermediate Backend Engineer, Security Factory: Code Security

An overview of this role

As an Intermediate Backend Engineer on GitLab's Security Factory: Code Security team, you'll help developers find and fix security issues in the code they write and the open source components they depend on.

Your work connects dependency analysis, vulnerability detection, and automated remediation. You'll build parsing that tells the security analysis engine which libraries and frameworks a project uses, extend a service that turns security advisories into dependency update merge requests, and develop hybrid analyzers that combine rule-based detection with artificial intelligence (AI) reasoning. You'll help evaluate how well those analyzers find real vulnerabilities and expand coverage of libraries, frameworks, and AI agent tooling.

We use AI-assisted development tools in our daily work and expect you to use them effectively and with good judgment.

What you’ll do

• Develop secure, well-tested, performant parsing for dependency manifests, lockfiles, and software bills of materials (SBOMs). Extend support for new package ecosystems and formats in the analysis engine and remediation service.
• Build and apply analyzers that combine deterministic analysis with AI-driven analysis, working with the team's technical leadership. Review their results and measure false positives and missed findings against benchmark applications with known vulnerabilities.
• Create detection rules mapped to Common Weakness Enumeration (CWE) and the test fixtures that prove they work.
• Contribute to packaging analyzers for continuous integration (CI) jobs, AI agent workflows, and command-line tools, reporting findings in GitLab's standard security report formats.
• Extend the automated remediation service, from running dependency updates in a sandbox to opening merge requests.
• Solve technical problems of moderate scope and complexity. Identify technical debt that slows the team down, and propose and implement improvements.
• Write maintainable code that meets our internal standards, and help maintain those standards through code review.
• Participate in on-call rotations to troubleshoot product operations, security operations, and urgent engineering issues.

What you’ll bring

• Experience using AI or large language model (LLM) tools to generate or evaluate technical content, with the judgment to know when output is trustworthy and when it isn't.
• Solid professional experience writing and testing production code in a systems language, particularly Go and/or Rust. We use both, plus Ruby for remediation and Python for some analyzers, and value a willingness to work across them.
• A willingness to learn how vulnerabilities arise in code and the software supply chain, explore common vulnerability classes such as the Open Worldwide Application Security Project (OWASP) Top 10 and CWE, and apply static analysis to detect them. Deep expertise isn't required, and we'll help you develop it.
• The ability to organize your work and follow through on tasks independently in a remote, largely asynchronous environment.
• The ability to communicate clearly and concisely about technical problems and propose iterative solutions.
• Helpful, but not required: experience with containerized workflows and continuous integration and continuous delivery (CI/CD), or a willingness to learn them; package managers and dependency tooling such as npm, Maven, pip, Bundler, or Cargo; web or mobile frameworks; parsing, abstract syntax trees (ASTs), program analysis, or detection rules; or evaluating AI-driven detection against labeled data. We use Docker heavily.

About the team

The Security Factory: Code Security team builds GitLab's code-level security scanning capabilities, spanning static application security testing (SAST) and dependency scanning.

We work closely with the Static Analysis team on GitLab's SAST engines, with Composition Analysis on the broader software supply chain, and with other groups across the Sec section. We rely heavily on asynchronous work across time zones.