AI Engineer

at GitLab

📍 United States

USD 108,400-129,600 per year

MIDDLE

✅ Remote

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 3 API @ 3 CI/CD @ 3 Customer Support GraphQL @ 3 JavaScript @ 6 LLM Marketing Mentoring @ 3 Prioritization @ 3 Prompt Engineering @ 3 Python @ 6 RAG Salesforce @ 2 Scoping @ 3 TypeScript @ 6 Workato @ 2

Details

GitLab is seeking an AI Engineer to help build the foundation for its transformation into an AI-first company. Reporting to the Director of Enterprise AI, this role is responsible for delivering internal AI-powered solutions that drive measurable business outcomes in a remote, asynchronous environment.

The initial focus will span Sales, Marketing, and Customer Support, embedding AI solutions into key systems and workflows. The role covers the full lifecycle from problem discovery and technical design through implementation, deployment, measurement, and iteration.

Responsibilities

Diagnose business problems before building solutions by mapping workflows, identifying constraints, and determining whether AI is the appropriate 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, including rapid prototypes, with a focus on practical outcomes and measurable business value.
Improve organizational flow by reducing bottlenecks, shortening lead times, and increasing throughput.
Measure success using flow metrics, adoption, return on investment, business metrics, and feedback loops.
Integrate AI capabilities into existing systems and workflows using APIs, orchestration tools, modern AI platforms, and the GitLab Duo Agent Platform where appropriate.
Leverage and showcase GitLab's AI offerings as a customer-zero user and provide real-world usage insights to research and development teams.
Partner with stakeholders across functions to understand constraints, bridge technical and non-technical perspectives, and align on outcomes.
Evaluate tools, document technical patterns, and create reusable foundations that help the team scale its impact.

Requirements

Strong interest in both foundational and emerging technology, with the judgment to choose simple, effective solutions rather than using new technology unnecessarily.
Competent coding skills and the ability to build end-to-end solutions, write clean and maintainable code, debug effectively, and deliver production-quality work independently.
Strong proficiency in at least one modern scripting language, such as Python or JavaScript/TypeScript.
Solid understanding of REST APIs, GraphQL, and integration patterns.
Practical experience with modern AI technologies, including prompt engineering, system prompts, context-window management, multi-turn interactions, output-quality evaluation, and systematic prompt iteration.
Understanding of model selection and cost-performance trade-offs, including fine-tuned models, large language models, retrieval-augmented generation, and context-window strategies.
Experience with agentic architecture patterns, including tool use, multi-agent orchestration, human-in-the-loop designs, guardrails, evaluation frameworks, and production reliability patterns.
Practical fluency with models from Anthropic, OpenAI, and open-source alternatives.
Understanding of AI safety risks and guardrails, including input validation, output filtering, access controls, prompt-injection defenses, and data-leakage prevention.
Strong systems thinking and diagnostic skills, including workflow mapping, bottleneck identification, and root-cause analysis.
Familiarity with enterprise business systems such as Salesforce, Marketo, Zendesk, Workato, Relevance AI, and Glean, as well as enterprise data models and workflows.
Ability to work with stakeholders across diverse business domains and understand their needs.
Track record of owning complex initiatives from discovery through delivery and driving measurable outcomes independently.
Product mindset, including MVP scoping, prioritization, iterative delivery, adoption, user experience, and business outcomes.

Preferred Requirements

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 such as n8n, Make, or Workato alongside custom development.
Previous startup or high-growth company experience.
Experience mentoring or leading technical projects with junior engineers.

Team

The Enterprise Technology & AI team drives transformation in how GitLab team members make decisions, operate at scale, and deliver results for customers. The team works in an all-remote, asynchronous setting guided by GitLab's values of collaboration, results, efficiency, diversity, inclusion and belonging, iteration, and transparency.