Senior Software Engineer, Security Factory: Code Security

VulnU; Northern (KY); Remote; USD 140.000 - 190.000; Vollzeit

Zusammenfassung

GitLab is seeking a Senior Backend Engineer for the Security Factory: Code Security team. You will build analyzers combining deterministic rules with AI reasoning, parsing dependencies, and shipping automated dependency update workflows.

You will own design through delivery, mentor peers, and contribute to secure, scalable tooling across CI/CD and agent environments. The role emphasizes Go and Rust proficiency, experience with build tooling, and strong collaboration with Security teams to

Qualifikationen

• Experience building your own LLM tooling, such as a harness, an agent pipeline, or evaluations.
• Substantial professional experience writing and testing production code in a systems language, particularly Go and/or Rust.
• Familiarity with package managers and dependency management across ecosystems (npm, Maven, pip, Bundler, Cargo).
• Demonstrated application security experience, such as vulnerability research, secure code review, or writing detection rules.

Aufgaben

• Act as the directly responsible individual (DRI) for team initiatives from design through delivery, shipping with minimal guidance.
• Design and ship analyzers that pair deterministic analysis with AI-driven analysis, and build evaluation harnesses.
• Package analyzers for CI jobs, AI agent workflows, and CLI tools with standard security report formats.
• Mentor engineers and participate in on-call rotations to assist troubleshooting and incidents.

Kenntnisse

Go

Rust

Ruby

Python

CI/CD

Remote work

Ausbildung

Bachelor's degree in Computer Science

Tools

Docker

Git

Kubernetes

Jobbeschreibung

As a Senior Backend Engineer on GitLab's Security Factory: Code Security team, you help developers find and fix security issues. Those issues live in the code they write and in the open source components they depend on.Your work spans complementary parts of a complete security analysis. On the dependency analysis side, you teach the analysis engine what a project depends on. You parse dependency manifests, lockfiles, and SBOMs so the engine knows which libraries and frameworks are in play and how the code uses them. You also extend the service that turns security advisories into automated merge requests that update vulnerable dependencies. On the vulnerability detection side, you grow GitLab's security analysis engine with hybrid analyzers that blend rule-based detection and AI reasoning. You build and apply the tooling that develops, evaluates, and ships those analyzers, and you measure how well they find real problems. That work also expands coverage of the libraries, frameworks, and AI agent tooling that real-world applications are built on.These threads reinforce each other. What a project depends on, and how its code uses those dependencies, are parts of one picture, and this team works across all of it. We make thoughtful use of AI-assisted development tools in our daily work. We expect you to use them effectively and with good judgment.What you doAct as the directly responsible individual (DRI) for team initiatives from design through delivery, shipping with minimal guidance in partnership with the technical leadBring systems built by one engineer to team ownership through documentation, tests, and shared reviewDesign and ship analyzers that pair deterministic analysis capabilities with AI-driven analysis, and build the evaluation harnesses that measure their false positives and missed findings against benchmark applications with known vulnerabilities, raising the bar for what counts as a trustworthy result. That includes detection rules mapped to CWE and the test fixtures that prove they work.Package those analyzers for every place GitLab runs them, including CI jobs, AI agent workflows, and command-line tools, with findings reported in GitLab's standard security report formatsDesign and ship the manifest, lockfile, and SBOM parsing that tells the static analysis engine what a project depends on, and extend it to new ecosystems and formatsShip features across the automated remediation service that turns security advisories into dependency update merge requests, from sandboxed updates to merge request creationSolve technical problems of high scope and complexity, actively seek out difficult impediments affecting the whole team, and advocate for improvements to quality, security, and performance with Product Management, Engineering stakeholders such as Frontend and UX, and partner teams such as Code Scanning and Composition AnalysisMentor Intermediate engineers through code review and pairing, and maintain our internal standards for style, maintainability, and best practices through reviewParticipate in on-call rotations to assist troubleshooting product operations, security operations, and urgent engineering issuesWhat you bringExperience building your own LLM tooling, such as a harness, an agent pipeline, or evaluations, with the judgment to know when output is trustworthy and when it isn'tSubstantial professional experience writing and testing production code in a systems language, particularly Go and/or Rust, with depth in at least one. We use both, plus Ruby on the remediation side and Python for some analyzers, and value willingness to work across them.Familiarity with package managers and dependency management in one or more language ecosystems, such as npm, Maven, pip, Bundler, or Cargo. Experience building tooling around them is better still.Demonstrated application security experience, such as vulnerability research, secure code review, or writing detection rules, and fluency with vulnerability classes (OWASP Top 10, CWE) and the software supply chainA track record of taking ownership of ambiguous problems and shipping with minimal guidance, with the self-motivation and organizational skills suited to a remote, largely asynchronous environmentDemonstrated capacity to communicate clearly and concisely about technical problems, and to write design proposals that bring a team to a decisionHelpful experienceExperience evaluating AI-driven detection against labeled data, including measuring false positives and missed findingsExperience with performance optimization at scaleHands-on program analysis experience, such as parsing, ASTs, or data-flow analysisFamiliarity with popular web or mobile application frameworks and how they handle input, data, and configurationExperience with containerized workflows and CI/CD (we use Docker heavily)About the teamThe Security Factory: Code Security team builds GitLab's code-level security scanning capabilities, spanning static application security testing and dependency scanning. We help developers find and fix security issues in both the code they write and the open source components they depend on, as early as possible.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.Remote-Global