Senior AI Engineer

An overview of this role

As a Senior 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.

Your initial focus will span Sales, Marketing, and Customer Support, where you will embed AI solutions into key systems and workflows.

What you'll do

• 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.
• Improve organizational flow by building solutions that reduce bottlenecks, shorten lead times, and increase throughput.
• Integrate AI capabilities into existing systems and workflows using APIs, orchestration tools, and modern AI platforms, including GitLab Duo Agent Platform.
• Be Customer Zero: leverage and showcase GitLab's AI offerings wherever possible.
• Partner closely with stakeholders across functions to understand the real constraints.
• Define and track success through business metrics, flow metrics, and feedback loops.
• Contribute to technical direction by evaluating tools, documenting patterns, and creating reusable foundations.

What you'll bring

• A Technologist at Heart
• Competent, Confident Coding Skills
• AI & LLM Technical Depth — Strong proficiency in Python, JavaScript/TypeScript, or similar, with REST APIs, GraphQL. Deep, practical experience with prompt engineering, structured multi-turn interactions, and iterating on prompt design.
• Model selection and cost-performance trade-offs: understanding when a smaller fine-tuned model outperforms a general-purpose large one, when RAG is the right architecture versus expanding the context window.
• 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.
• AI Safety & Risk Awareness — Designing appropriate guardrails (input validation, output filtering, access controls, prompt injection defences, and data leakage prevention).
• Systems Thinking & Diagnostic Rigour
• Business System Expertise — Salesforce, Marketo, Zendesk, Workato, Relevance AI, Glean.
• Broad Functional Understanding
• End-to-End Ownership
• Product Mindset

Preferred requirements

• Experience with GitLab platform and CI/CD workflows
• Background in consulting, solutions engineering, or customer-facing technical roles
• 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
• Previous startup or high-growth company experience
• Experience mentoring or leading technical projects with junior engineers

About the team

You will join the Enterprise Technology & AI team. We work in an all-remote, asynchronous setting, guided by GitLab's values.