Senior Backend Engineer, Architecture Engineering: Nonlinear Productivity

GitLab; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

GitLab is seeking a Senior Backend Engineer on the Nonlinear Productivity team to remove friction in the software development lifecycle with AI-powered automation.

You will diagnose long review cycles and brittle automation, build reliable agentic workflows, and ship systems that you can trust for engineering decisions.

You’ll work across GitLab’s codebase, evaluate generated outputs for correctness and cost, and help scale deployments across self-managed and multi-tenant environments.

Responsibilities

• Identify sources of friction across GitLab's software development lifecycle and scope agentic solutions to address them, turning vague pain points into concrete, buildable proposals.
• Design and build reliable AI-powered systems that follow step-by-step workflows, use tools and safety checks, and correct errors before taking engineering action — the kind of output you can actually trust with real engineering decisions.
• Build and maintain evaluation tools that judge agent output on correctness, constraint compliance, and cost, not on whether it merely "seems to work."
• Work across GitLab's codebase as each problem requires, going wherever the friction actually is rather than staying inside one service or product area.
• Apply distributed systems judgment to identify generated code that may fail under concurrency, at scale, or across self-managed, dedicated, and multi-tenant deployments, catching failures before they reach custome

Job 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 valuesand 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 Backend Engineer on GitLab's Nonlinear Productivity team, you'll find and remove friction across the software development lifecycle using reliable AI-powered automation — diagnosing problems like long review cycles, manual release steps, and brittle automation, then building the automation and process changes that resolve them for good.

Some examples of the problems this team takes on:

• Cutting the time it takes to complete a good code review — one that still keeps a human in the loop — by half, using agentic solutions.
• Turning a manual, error-prone release step into an agentic workflow that catches its own mistakes before a human ever has to.

What you’ll do

• Identify sources of friction across GitLab's software development lifecycle and scope agentic solutions to address them, turning vague pain points into concrete, buildable proposals.
• Design and build reliable AI-powered systems that follow step-by-step workflows, use tools and safety checks, and correct errors before taking engineering action — the kind of output you can actually trust with real engineering decisions.
• Build and maintain evaluation tools that judge agent output on correctness, constraint compliance, and cost, not on whether it merely "seems to work."
• Work across GitLab's codebase as each problem requires, going wherever the friction actually is rather than staying inside one service or product area.
• Apply distributed systems judgment to identify generated code that may fail under concurrency, at scale, or across self-managed, dedicated, and multi-tenant deployments, catching failures before they reach custome