GitLab is the intelligent orchestration platform for DevSecOps.
Enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation.
More than 50 million registered users and more than 50% of the Fortune 100 trust GitLab.
AI is embraced as a core productivity multiplier; all team members are expected to incorporate AI into their daily workflows.
Responsibilities
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; review results and measure false positives and missed findings against benchmark applications.
Create detection rules mapped to Common Weakness Enumeration (CWE) and the test fixtures that prove they work.
Contribute to packaging analyzers for 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 and propose and implement improvements.
Write maintainable code that meets 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.
Requirements
Experience using AI or large language model (LLM) tools to generate or evaluate technical content, with judgment to know when output is trustworthy.
Solid professional experience writing and testing production code in a systems language, particularly Go and/or Rust; Ruby for remediation and Python for some analyzers.
Willingness to learn how vulnerabilities arise in code and the software supply chain, explore common vulnerability classes such as OWASP Top 10 and CWE, and apply static analysis to detect them.
Ability to organize work and follow through on tasks independently in a remote, largely asynchronous environment.
Ability to communicate clearly and concisely about technical problems and propose iterative solutions.
Helpful but not required: containerized workflows and CI/CD; 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; evaluating AI-driven detection against labeled data. Docker used heavily.