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 a Senior Software Engineer, you'll build and deliver autonomous, agentic software development lifecycle capabilities for GitLab's engineering teams. You'll lead technical execution, mentor other engineers, and work closely with Product Managers, engineers, and AI and machine learning partners. You'll turn complex requirements into robust, secure, and performant AI-driven solutions, with a focus on high-quality code, reliable systems, measurable performance, and safe use of AI across the software development lifecycle.

What you’ll do

• Build autonomous, agentic software development lifecycle features that support team goals and GitLab's product roadmap.
• Develop and deploy AI agents that automate engineering tasks such as merge request authoring, test generation, and security remediation.
• Collaborate with Product and AI and machine learning teams to break down complex requirements and deliver solutions iteratively.
• Write clean, maintainable code and conduct thorough code reviews to support the quality and safety of agentic workflows.
• Build and maintain orchestration patterns and safety guardrails for AI services.
• Measure and improve the performance, latency, and correctness of AI-driven features using defined evaluation frameworks.
• Participate in on-call rotations and debug complex issues involving AI services and autonomous agents.
• Follow GitLab's security, compliance, and data governance standards while contributing to documentation, playbooks, reusable libraries, and the growth of other engineers.

What you’ll bring

• Experience building and shipping production-grade software applications, including transferable experience from related engineering domains.
• Experience with AI and machine learning application programming interfaces, large language models, or agentic frameworks in a web development context.
• Proficiency in a modern programming language such as Ruby, Go, or Python, along with experience working with distributed systems.
• Strong understanding of the software development lifecycle, continuous integration and continuous delivery, and developer tools.
• Experience with testing frameworks, observability tools, and performance monitoring.
• Ability to communicate technical concepts clearly and collaborate across functions.
• Experience writing maintainable code, reviewing others' work, and supporting secure, reliable systems.
• Ability to mentor junior and intermediate engineers and help them develop their technical skills and understanding of AI patterns.

About the team

We build agentic capabilities that improve how software is planned, developed, tested, secured, and maintained. We work with Product and AI and machine learning partners to deliver safe, reliable automation for our internal workflows and GitLab product features, while sharing reusable patterns and practical guidance across engineering.