About GitLab
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.
An overview of this role
As an Intermediate Backend Engineer (Python) in GitLab's Agent Foundations stage, you'll go beyond using AI tools. You'll help build the foundations for GitLab's agentic AI experiences: the platform that lets AI agents work across the whole software delivery lifecycle, not just write code. That covers the reusable building blocks agents and flows are made from as well as our core harness, Duo Developer.
Most of your work will be backend engineering in Python, using libraries such as LangGraph to build secure, reliable and scalable features in our AI Gateway. You'll also work across the stack where needed. You'll work closely with engineers across the stage and other AI Engineering teams. This is a high-visibility area where GitLab's core platform meets its AI strategy.
What you'll do
- Develop, ship and maintain features for the Duo Agent Platform in the Duo Workflow Service, the AI Gateway and, where needed, the GitLab monolith. Keep them secure, well-tested and performant.
- Build and improve agentic flows and their reusable parts with LangChain and LangGraph, including the Flow Registry.
- Work with Product Management, UX, frontend, backend and AI specialists to refine requirements and ship improvements in small iterations.
- Design, implement and review APIs (including GraphQL and REST) and the backend logic behind them, with reliable, scalable and clear contracts for clients such as the GitLab monolith, IDE extensions and Duo CLI.
- Improve and extend automated testing (pytest and other frameworks), including evaluations of agent and flow behavior, to strengthen quality and give developers faster feedback.
- Share standards, patterns and learnings with other engineers to raise the bar for responsible AI integration and evidence-driven engineering.
- Join Tier 2 on-call rotations to troubleshoot production issues, contribute to root cause analysis, and improve observability and resiliency.
- Keep an eye on the competitive landscape to help keep GitLab's agent platform best-in-class as more work becomes agentic.
About the team
The Agent Foundations stage builds the foundations for GitLab's agentic AI experiences. We provide the platform, catalog and execution features that help teams deliver resilient agents and flows to customers. The stage has three groups: Agent Developer, AI Catalog and Agent Execution. Between them, they own the GitLab Duo Developer foundational flow and the Flow Registry; the AI Catalog, including custom agents, custom flows and external agent integrations; and agent execution, agent tools and agent observability.
Our engineers work async-first across EMEA, AMER, and India timezones. We work with teams across AI engineering and the rest of GitLab so the Duo Agent Platform can power many of GitLab's AI features.
How GitLab Supports Full-Time Employees
- Benefits to support your health, finances, and well-being
- Flexible Paid Time Off
- Team Member Resource Groups
- Equity Compensation & Employee Stock Purchase Plan
- Growth and Development Fund
- Parental Leave
What you'll bring
- Experience building and maintaining production Python backend applications, including APIs, asynchronous or background processing, and data models.
- Experience with LLM application frameworks such as LangGraph, or designing and shipping AI-powered backend features or harnesses.
- Skill in designing or extending APIs (REST, GraphQL or gRPC) with attention to scalability, maintainability and backward compatibility.
- Comfort working across the stack in a mature codebase. Familiarity with Ruby on Rails and/or JavaScript and Vue is a plus.
- Experience finding and fixing performance bottlenecks in applications.
- Clear written and verbal communication, including technical proposals and documentation, in a remote, async, cross-functional team.
- Openness to learning and to applying skills from related technologies or fields.
