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HomeJobsAI Engineer

GitLab

AI Engineer

full timeseniorRemoteRemote2 months ago
25,000-40,000 AED/mo
AI & Machine Learning

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 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 AI Engineer at GitLab, you'll help build the foundation for GitLab's transformation into an AI-first company. Reporting to the Director, Enterprise AI, you'll be a hands-on technical leader responsible for delivering internal AI-powered solutions that drive measurable business outcomes. Building fast matters, but it's not enough on its own. This role starts with understanding the real problem: mapping how work moves across teams, tools, and handoffs, identifying the true constraint, and validating whether AI is the right solution before you begin development. From there, you'll take ownership from discovery through deployment, combining strong engineering skills with systems thinking and business understanding. Your initial focus will span Sales, Marketing, and Customer Support, where you will embed AI solutions into key systems and workflows. This role offers the opportunity to shape how GitLab team members work, improve flow across the organization, and help advance our mission in a remote, asynchronous, and values-driven environment. What you'll do - Diagnose business problems before building solutions. Map workflows, identify constraints, and confirm whether AI is the right intervention. Be prepared to say "this doesn't need AI" when that's the honest answer. - Own AI initiatives end-to-end, from stakeholder discovery and technical design through implementation, deployment, and iteration. - Design, develop, and ship AI-powered solutions quickly, delivering working prototypes in days, not months, with a focus on practical outcomes and measurable business value. - Improve organizational flow by building solutions that reduce bottlenecks, shorten lead times, and increase throughput. Measure success using flow metrics alongside adoption and ROI. - Integrate AI capabilities into existing systems and workflows using APIs, orchestration tools, and modern AI platforms, including GitLab Duo Agent Platform, where appropriate. The right tool wins, whether that's custom code, a platform, or a well-crafted prompt. - Be Customer Zero: leverage and showcase GitLab's AI offerings wherever possible, feeding real-world usage insights back to R&D. - Partner closely with stakeholders across functions to understand the real constraints. Ask the right questions, bridge technical and non-technical perspectives, and align on outcomes before jumping to solutions. - Define and track success through business metrics, flow metrics, and feedback loops that make performance visible and actionable. - Contribute to technical direction by evaluating tools, documenting patterns, and creating reusable foundations that help the team scale its impact. What you'll bring - A Technologist at Heart - Genuinely invested in technology, the foundational and the cutting-edge in equal measure. You're as energised by a well-designed API integration as you are by the latest foundation model release. You reach for the simplest solution that solves the problem well, rather than forcing new technology when proven approaches would do. AI is a powerful part of your toolkit, but it sits on top of solid engineering fundamentals, not in place of them. - Competent, Confident Coding Skills - You can build working solutions end-to-end, write clean and maintainable code, and debug effectively. Whether your skills were honed in a traditional engineering role, through building automations, or shipping side projects, what matters is that you can deliver production-quality work independently. - AI & LLM Technical Depth - Strong proficiency in at le

Requirements

  • What you'll bring
  • - A Technologist at Heart - Genuine investment in technology, foundational and cutting-edge in equal measure. Energised by both API integration and the latest foundation model releases. Prefer simple, effective solutions over over-engineering; AI is a powerful tool on top of solid engineering fundamentals.
  • - Competent, Confident Coding Skills - Ability to build end-to-end solutions, write clean, maintainable code, and debug effectively. Production-quality work delivered independently.
  • - AI & LLM Technical Depth - Strong proficiency in AI/LLM technologies and practical application in real systems.
  • - Other expectations inferred from role: ability to design, implement, and deploy AI-powered solutions; integration with APIs and orchestration tools; collaboration with cross-functional teams; focus on measurable business value.

Responsibilities

  • What you'll do
  • - Diagnose business problems before building solutions: map workflows, identify constraints, confirm AI is the right intervention, and acknowledge when AI isn’t needed.
  • - Own AI initiatives end-to-end: stakeholder discovery, technical design, implementation, deployment, and iteration.
  • - Design, develop, and ship AI-powered solutions quickly, delivering working prototypes in days with measurable business value.
  • - Improve organizational flow by reducing bottlenecks, shortening lead times, and increasing throughput; measure success with flow metrics, adoption, and ROI.
  • - Integrate AI capabilities into existing systems and workflows using APIs, orchestration tools, and modern AI platforms, including GitLab Duo Agent Platform where appropriate.
  • - Be Customer Zero: showcase GitLab's AI offerings and feed usage insights back to R&D.
  • - Partner with stakeholders across functions to understand constraints, bridge technical and non-technical perspectives, and align on outcomes before solutioning.
  • - Define and track success through business metrics, flow metrics, and feedback loops for visibility and actionability.
  • - Contribute to technical direction by evaluating tools, documenting patterns, and creating reusable foundations to scale impact.

Skills Required

API integrationAI/LLM technologiesorchestration toolsGitLab Duo Agent Platformprototype developmentend-to-end solution deliveryproduction-quality codingsystems thinkingworkflow/process optimizationstakeholder collaborationtechnical designdeployment of AI-powered solutions

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