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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 [https://www.youtube.com/watch?v=OuZIb5zszQI] 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 20
25. 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 Staff Backend Engineer (AI) in the Verify stage at GitLab, you'll help
shape and scale the core infrastructure behind GitLab CI. You'll play a central
role in how we integrate AI into CI/CD workflows. Your work will impact
performance, reliability, and usability for people running millions of CI jobs,
from small teams to the largest enterprises.
AI is a top priority in the year ahead. In this role, you'll go beyond using AI
tools and help define how we design, build, and iterate on AI-assisted and
agentic CI experiences. You'll set standards for what good looks like across our
AI agent portfolio, including how we measure success, how we instrument behavior
in production, and how we account for large language model limitations. You'll
also help responsibly integrate GitLab's Duo Agent Platform into CI workflows at
scale, on a foundation that's fast, reliable, secure, and observable.
We have ambitious goals for Agentic CI in FY27
[https://gitlab.com/groups/gitlab-org/-/work_items/20586]. As a Staff Engineer,
you will:
• Partner with Engineering, Product, and UX leadership to pressure-test our
priorities: where we can move faster, where we're missing data, and where
there's whitespace to innovate. Part of this includes learning and growing
with the Engineering team you will collaborate closely with.
• Define what success looks like across our agent portfolio and make sure we're
tracking against it — not just shipping, but learning.
• Bring a sharp eye to the competitive landscape, helping us understand what it
takes to keep GitLab CI best-in-class in an increasingly agentic world.
• Examples of Agentic CI work we have planned for the upcoming year:
• AI Pipeline Builder
[https://gitlab.com/groups/gitlab-org/-/work_items/20443], the
foundational CI agent that auto-creates pipelines for new projects and
serves as the launchpad for onboarding new CI users.
• Automate the Fix a Failing Pipeline flow
[https://gitlab.com/gitlab-org/gitlab/-/work_items/588753] at scale – from
dogfooding on internal GitLab projects through to safe, controlled rollout
for customers, solving real infrastructure and scalability challenges.
• Build the instrumentation and observability
[https://gitlab.com/groups/gitlab-org/-/work_items/20904] layer that makes
agentic CI trustworthy — trigger volume dashboards, retry rates, cost
safeguards — so we can measure what's working, catch what isn't, and
iterate with confidence.
• Harden the CI pipeline execution infrastructure that these agents depend
on: database access patterns, background processing, and job orchestration
built to handle the additional load that AI-driven automation introduces
at enterprise scale.
WHAT YOU’LL DO
• Shape and scale GitLab CI backend infrastructure to improve performance,
reliability, and usability for users running jobs at high volume.
• Design and implement AI-powered features for Agentic CI, including agents,
agentic flows, and LLM-backed tooling that integrates with GitLab's Duo Agent
Platform.
• Define what success looks like for AI in CI before you build, including
baselines, measurable outcomes, and clear signals that help the team learn
and iterate.
• Build the instrumentation and observability needed to make AI-assisted CI
trustworthy in production, including feature behavior metrics, dashboards,
and safeguards.
• Own and drive measurable performance improvements across CI systems (for
example, database access patterns, background processing, and job
orchestration) by forming hypotheses, running experiments, and validating
results with data.
• Write secure, well-tested, maintainable Ruby on Rails code in a large
monolith, improving existing features while reducing technical debt and
operational risk.
• Lead cross-functional technical work with Product, UX, and Infrastructure,
influencing architecture and execution across the Verify stage.
• Share standards, patterns, and learnings with other engineers, raising the
bar for responsible AI integration and evidence-driven engineering across CI.
WHAT YOU’LL BRING
• Advanced proficiency with Ruby and Ruby on Rails, with experience building
and maintaining reliable backend services in a large codebase.
• Strong PostgreSQL skills, including data modeling, query tuning, and scaling
large tables through proactive performance investigation and remediation.
• Hands-on experience building, running, and debugging high-traffic production
systems, ideally in CI, workflow orchestration, or adjacent
infrastructure-heavy domains.
• Practical experience designing and shipping AI-powered backend features and
integrations, including sound judgment about large language model limitations
and responsible use in production.
• A data-driven approach to engineering: defining hypotheses, establishing
baseline metrics, instrumenting changes, and measuring outcomes against clear
success criteria.
• Familiarity with observability patterns and tools (metrics, logging, tracing)
to diagnose issues, improve reliability, and guide iteration.
• Strong backend architecture and delivery practices, including secure design,
well-tested code, and strategies for safe rollouts and zero-downtime changes.
• Clear written and verbal communication skills, including writing technical
proposals and documentation, and collaborating effectively in a remote,
asynchronous, cross-functional environment.
ABOUT THE TEAM
The Verify stage focuses on collaboration, iteration, and helping GitLab users
run fast, reliable, and scalable Continuous Integration (CI) pipelines for
projects of all sizes, from small teams to large enterprises. For more on how we
work, see Team Handbook Page
[https://handbook.gitlab.com/handbook/engineering/devops/verify/] and Related
Initiative.
Remote-Global
HOW GITLAB SUPPORTS FULL-TIME EMPLOYEES
• Benefits to support your health, finances, and well-being
[https://about.gitlab.com/handbook/total-rewards/benefits/general-and-entity-benefits/]
• Flexible Paid Time Off
[https://handbook.gitlab.com/handbook/people-group/time-off-and-absence/time-off-types/#flexible-paid-time-off-pto]
• Team Member Resource Groups
[https://handbook.gitlab.com/handbook/company/culture/inclusion/tmrg-tmag/]
• Equity Compensation & Employee Stock Purchase Plan
[https://handbook.gitlab.com/handbook/total-rewards/stock-options/]
• Growth and Development Fund
[https://handbook.gitlab.com/handbook/people-group/learning-and-development/growth-and-development/]
• Parental Leave
[https://about.gitlab.com/handbook/total-rewards/benefits/general-and-entity-benefits/#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
[https://about.gitlab.com/company/culture/inclusion/#examples-of-select-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.
Privacy Policy: Please review our Recruitment Privacy Policy.
[https://handbook.gitlab.com/handbook/hiring/candidate-faq/recruitment-privacy-policy/]
Your privacy is important to us.
GitLab is proud to be an equal opportunity workplace and is an affirmative
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employment, career development and advancement, promotion, and retirement are
based solely on merit, regardless of race, color, religion, ancestry, sex
(including pregnancy, lactation, sexual orientation, gender identity, or gender
expression), national origin, age, citizenship, marital status, mental or
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disabled veterans, recently separated veterans, active duty wartime or campaign
badge veterans, and Armed Forces service medal veterans), or any other basis
protected by law. GitLab will not tolerate discrimination or harassment based on
any of these characteristics. See also GitLab’s EEO Policy
[https://about.gitlab.com/handbook/people-policies/inc-usa/#equal-employment-opportunity-policy] and EEO
is the Law
[https://about.gitlab.com/handbook/labor-and-employment-notices/#eeoc-us-equal-employment-opportunity-commission-notices].
If you have a disability or special need that requires accommodation
[https://about.gitlab.com/handbook/people-policies/inc-usa/#reasonable-accommodation],
please let us know during the recruiting process
[https://about.gitlab.com/handbook/hiring/interviewing/#adjustments-to-our-interview-process].