data
Posted 1 weeks agoAI Engineer
at GitLab
United StatesRemote
Responsibilities
- Diagnose business problems before building solutions.
- Map workflows, identify constraints, and confirm whether AI is the right intervention.
- 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.
- Define and track success through business metrics, flow metrics, and feedback loops that make performance visible and actionable.
- End-to-End Ownership - Track record of owning complex initiatives from discovery through delivery. Comfortable operating with ambiguity and driving to measurable outcomes independently.
Requirements
- GitLab is the intelligent orchestration platform for DevSecOps.
- 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.
- 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.
- 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.
- Your initial focus will span Sales, Marketing, and Customer Support, where you will embed AI solutions into key systems and workflows.
- Be prepared to say "this doesn't need AI" when that's the honest answer.
- Be Customer Zero: leverage and showcase GitLab's AI offerings wherever possible, feeding real-world usage insights back to R&D.
- You're as energised by a well-designed API integration as you are by the latest foundation model release.
- AI is a powerful part of your toolkit, but it sits on top of solid engineering fundamentals, not in place of them.
- 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 least one modern scripting language (Python, JavaScript/TypeScript, or similar) and a solid understanding of REST APIs, GraphQL, and integration patterns. Deep, practical
- experience with modern AI technologies, specifically: Prompt engineering as a core discipline: designing effective system prompts, managing context windows, structuring multi-turn interactions, evaluating output quality, and iterating systematically on prompt design.
- Agentic architecture patterns: tool use, multi-agent orchestration, human-in-the-loop designs, guardrails, evaluation frameworks, and production-grade reliability patterns.Practical fluency across the LLM ecosystem: hands-on
- experience with models from Anthropic, OpenAI, open-source alternatives, and the judgment to know which to reach for and when.
- AI Safety & Risk Awareness - You think critically about how the solutions you build could be exploited, misused, or produce unintended consequences.
- You know how to design appropriate guardrails (input validation, output filtering, access controls, prompt injection defences, and data leakage prevention) and you treat these as first-class engineering concerns.
- Systems Thinking & Diagnostic Rigour - The ability to look at a complex process and see the constraint.
- Business System Expertise - Familiarity with the landscape of enterprise business systems, CRM (Salesforce), marketing automation (Marketo), support platforms (Zendesk), integration and orchestration tools (Workato), AI platforms (Relevance AI), and enterprise search and knowledge tools (Glean). You don't need deep
- experience with all of these, but to understand what they do, how they fit together, and be willing to build with and across them.
- A strong understanding of enterprise data models and workflows is essential.
- Broad Functional Understanding - Ability to have meaningful conversations with stakeholders across diverse domains and quickly understand their unique needs.
- Experience with GitLab platform and CI/CD workflows
- Familiarity with value stream mapping, flow metrics, or Theory of Constraints thinking •
- Experience with low-code/no-code orchestration tools (n8n, Make, Workato) alongside custom development
- You will join the Enterprise Technology & AI team.
- We're the backbone of the organisation, driving transformation in how GitLab team members make decisions, operate at scale, and deliver results for our customers.
- We believe the best AI solutions start with understanding the system, not the technology.
- 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 have a disability or special need that requires accommodation , please let us know during the recruiting process .
Benefits
- 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.
- 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 $108,400 — $129,600 USD How GitLab Supports Full-Time Employees •
- Flexible Paid Time Off
- Equity Compensation & Employee Stock Purchase Plan
- Growth and Development Fund
- Parental Leave
Additional details
- More than 50 million registered users and more than 50% of the Fortune 100
- trust GitLab to ship better, more secure software faster.
- 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.
- 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.
- Building fast matters, but it's not enough on its own.
- The right tool wins, whether that's custom code, a platform, or a well-crafted prompt.