Backend Engineer (Python),AI Engineering: Agent Foundations

Description

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 (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.

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

Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application.

Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process.

Responsibilities

• 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.
• 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.