Senior AI Engineer

Stack

Responsibilities

• ▹Diagnose business problems before building solutions: map workflows, identify constraints, confirm AI is the right intervention
• ▹Own AI initiatives end-to-end, from stakeholder discovery through technical design, deployment, and iteration
• ▹Design, develop, and ship AI-powered solutions quickly, delivering working prototypes in days, not months
• ▹Improve organizational flow: reduce bottlenecks, shorten lead times, increase throughput
• ▹Integrate AI capabilities into existing systems and workflows using APIs, orchestration tools, and modern AI platforms (e.g. GitLab Duo Agent Platform)
• ▹Be Customer Zero: showcase GitLab's AI offerings and feed real-world usage insights back to R&D
• ▹Partner closely with stakeholders to understand real constraints and align on outcomes
• ▹Define and track success through business metrics, flow metrics, and feedback loops
• ▹Contribute to technical direction by evaluating tools and documenting reusable patterns

Requirements

• ▹Competent, confident coding skills: building working solutions end-to-end, clean maintainable code, effective debugging
• ▹Strong proficiency in at least one modern scripting language (Python, JavaScript/TypeScript, or similar), REST APIs, GraphQL, and integration patterns
• ▹Deep, practical experience with modern AI technologies: prompt engineering as a core discipline, context window management, multi-turn interactions, output quality evaluation
• ▹Understanding of model selection and cost-performance trade-offs: when a smaller fine-tuned model outperforms a general one, RAG vs. larger context windows
• ▹Familiarity with agentic architecture patterns: tool use, multi-agent orchestration, human-in-the-loop design, guardrails, evaluation frameworks
• ▹Practical fluency across the LLM ecosystem (Anthropic, OpenAI, open-source alternatives) and judgment on which to use when
• ▹AI safety and risk awareness: designing guardrails (input validation, output filtering, access controls, prompt injection defenses, data leakage prevention)
• ▹Systems thinking and diagnostic rigor: mapping complex processes and identifying bottlenecks and root causes
• ▹Familiarity with enterprise business systems: CRM (Salesforce), marketing automation (Marketo), support platforms (Zendesk), orchestration tools (Workato), AI platforms (Relevance AI), enterprise search (Glean)
• ▹Broad functional understanding and ability to have meaningful conversations across diverse stakeholders
• ▹Track record of end-to-end ownership on complex initiatives, comfortable operating with ambiguity
• ▹Product mindset: scoping MVPs, ruthless prioritization, iterative delivery

Nice to have

• ▹Experience with the 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

Soft skills

About the company

GitLab is the intelligent orchestration platform for DevSecOps, with more than 50 million registered users. The Enterprise Technology & AI team drives transformation in how GitLab makes decisions and delivers results, in a fully remote, asynchronous environment guided by GitLab's values.