Senior AI Engineer

Role Overview

Join GitLab as a Senior AI Engineer in a hands-on technical leadership role. You will help shape GitLab’s transition to an AI-first organization by delivering internal AI-powered solutions with measurable business impact.

Initial Focus Areas

• Sales
• Marketing
• Customer Support

Key Missions / Responsibilities

• Diagnose business problems before building solutions
  • Map workflows end-to-end, 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 solutions quickly
  • Deliver working prototypes in days, not months
  • Focus on practical outcomes, adoption, user experience, and measurable business value
• Operate with strong product and engineering judgment
  • Scope MVPs, prioritize ruthlessly, and iterate based on results

Required / Core Qualifications

• Broad functional and stakeholder understanding
  • Ability to conduct meaningful discussions across domains and quickly understand needs
• Product mindset
  • Ability to scope MVPs and deliver iteratively with outcomes in mind
• Systems thinking & diagnostic rigor
  • Map processes, identify bottlenecks, trace root causes, and ask what’s blocking flow before selecting a model
• Business system expertise (understanding of the enterprise landscape)
  • CRM: Salesforce
  • Marketing automation: Marketo
  • Support platforms: Zendesk
  • Integration/orchestration: Workato
  • AI platforms: Relevance AI
  • Enterprise search/knowledge: Glean
  • Solid understanding of enterprise data models and workflows
• End-to-end ownership
  • Experience owning complex initiatives from discovery through delivery; comfortable with ambiguity
• LLM cost/performance decision-making
  • Trade-offs between fine-tuned smaller models vs general-purpose large models
  • When RAG is appropriate vs other approaches (e.g., expanding context window)

AI / LLM Technical Depth

• Proficiency in at least one modern scripting language: Python or JavaScript/TypeScript (or similar)
• Strong understanding of REST APIs, GraphQL, and integration patterns
• Prompt engineering as a core discipline
  • System prompts, context window management, multi-turn structure, evaluation, and iterative improvement

AI Safety & Risk Awareness

• Design for security and misuse resistance
  • Guardrails such as input validation, output filtering, access controls, prompt injection defenses, and data leakage prevention

Nice-to-Haves / Strength Signals

• Technologist mindset: enjoy both pragmatic API integrations and cutting-edge model advancements
• Preference for simplest solutions that work; avoid forcing new tech without clear value