About the role
GitLab is the intelligent orchestration platform for DevSecOps. GitLab 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 to ship better, more secure software faster.
The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software.
*Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab.
An overview of this role
As an Intermediate Backend Engineer on GitLab's Security Factory: Code Scanning team, you'll help developers find and fix security issues in their code by contributing to the static analysis engine that finds them.
Your work spans both the engine and the tools we use to evaluate it. You'll extend how the engine models programs, from parsing source code and resolving symbols to building call graphs and tracking tainted data across files and languages. You'll also build and apply tooling to test its findings against benchmark applications with known vulnerabilities, measuring both false positives and missed vulnerabilities.
We build the engine with artificial intelligence (AI) agents that write and review code from written specifications, under human direction. You'll implement component specifications within the team's architecture, working with engineers and AI agents. Good judgment about when to trust agent output, and when to bring it to human review, is central to the role.
What you'll do
- Extend the program model, including parsing, symbol resolution, intermediate representations, call graphs, and taint and data-flow analysis, to support new languages and frameworks.
- Build and apply AI-assisted tooling to implement, review, and validate engine changes and findings, in collaboration with the team's technical leadership. Measure detection quality against known vulnerabilities, judging changes primarily on false positive and false negative rates.