Engineering Manager, Agent Foundations: Agent Execution

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 Engineering Manager for the Agent Execution group, you'll lead more than 10 engineers who build foundations for AI agents to run safely and effectively across GitLab. You'll give the group clarity, remove obstacles, and help teams move quickly while protecting what matters. You'll contribute to design reviews on sandboxing and agent observability, work alongside staff engineers, and use modern AI coding tools and agent harnesses in your work. What you’ll do - Lead the Agent Tools, Agent Observability, and Runner Execution teams across frontend, backend, and AI engineering, with each team anchored by a staff engineer. - Grow the group by hiring, onboarding, coaching, and developing engineers at every level. - Partner with product and UX to turn ambiguous problems into shipped milestones and make prioritization tradeoffs explicit. - Contribute substantively to technical design for running agents safely and effectively at scale. - Establish practical standards for the group's use of AI tools, including tool selection and configuration. - Coach engineers through ambiguity in a fast-changing technical space. - Represent the group across GitLab's AI organization and with the teams that depend on the GitLab Duo Agent Platform. What you’ll bring - Experience managing distributed engineering teams and working through technical leads and staff-level engineers. - Technical judgment developed through hands-on engineering experience and fluency with modern AI coding tools and agent harnesses. - Ability to guide teams in applying AI to software engineering workflows and technical decision-making. - Experience delivering results in fast-paced environments with ambiguous requirements. - A commitment to coaching and developing engineers in a positive, inclusive team environment. - Experience building and deploying AI products; working with sandboxing, container isolation, infrastructure security, observability systems, or reliability engineering; or using Python, Ruby, Go, or TypeScript is helpful. About the team We’re building the product and infrastructure that make GitLab an effective environment for running agents across the software development lifecycle. Our three teams, Agent Tools, Agent Observability, and Runner Execution, work on areas ranging from GitLab's Model Context Protocol (MCP) server and configurable network access to agent sandboxing and transparent agent interactions across GitLab. We’re distributed across three continents and partner with teams throughout GitLab to help the GitLab Duo Agent Platform become the backbone of GitLab's AI features. A Senior Engineering Manager currently leads our group on an interim basis and will support your onboarding and remain a close partner afterward. This is an opportunity to lead a consequential group as AI changes how software is built. The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity. Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $152,800—$172,800 USD How GitLab Supports Full-T

Experience managing distributed engineering teams and working through technical leads and staff-level engineers. Technical judgment developed through hands-on engineering experience and fluency with modern AI coding tools and agent harnesses. Ability to guide teams in applying AI to software engineering workflows and technical decision-making. Experience delivering results in fast-paced environments with ambiguous requirements. A commitment to coaching and developing engineers in a positive, inclusive team environment. Experience building and deploying AI products; working with sandboxing, container isolation, infrastructure security, observability systems, or reliability engineering; or using Python, Ruby, Go, or TypeScript is helpful.