AI Engineer responsible for building internal AI-powered solutions to drive business outcomes, focusing on Sales, Marketing, and Customer Support. The role involves diagnosing business problems, owning AI initiatives end-to-end, designing and shipping AI solutions quickly, and integrating AI capabilities into existing systems. Emphasis on practical outcomes, measurable business value, and improving organizational flow.

Senior Professional Services Technical Architect specializing in GitLab Duo Agent Platform, responsible for helping customers move from ideas to production by designing and delivering solutions, building and deploying Custom Agents, Custom Flows, and CI/CD integrations, and owning delivery end-to-end. This role involves customer discovery, integration with existing systems, establishing AI governance, and measuring impact.

This role is for a Principal Solutions Architect specializing in AI and Security & Compliance within the EMEA region. The primary focus is on acting as a trusted technical advisor and pre-sales partner to customers, helping them leverage GitLab's AI-powered DevSecOps platform. The role involves leading technical discovery, architecture design, and evaluations (POC/POV) for AI-driven solutions, driving AI-focused solution strategy, and influencing product direction with field feedback. The Solutions Architect will also mentor other team members and contribute to thought leadership.

Senior Backend Engineer (AI) at GitLab, focusing on integrating AI into CI/CD workflows. The role involves designing, building, and operating AI-assisted and agentic CI experiences, instrumenting and monitoring these systems, and hardening the underlying infrastructure. The primary focus is on scaling AI capabilities within the GitLab CI platform.

Staff Backend Engineer focused on AI Governance at GitLab, defining the technical foundation for governing GitLab Duo agents at enterprise scale. The role involves designing backend architecture for auditability, policy enforcement, and enterprise reporting, ensuring clear visibility and controls for AI agent activity. It requires strong experience in backend systems, authorization patterns, and Ruby on Rails/Python, with a focus on enabling secure and compliant adoption of AI features.

Engineering Manager for GitLab's AI Engineering: Workflow Catalog team, responsible for guiding a team of 9 engineers in building and scaling GitLab's AI catalog for agents and workflows. The role involves people management, technical judgment, and shipping customer-facing AI agent capabilities.

Senior Solutions Architect with AI and Platforms expertise to advise customers on GitLab's AI-powered DevSecOps platform, focusing on technical strategy, evaluations, and driving adoption of AI-led solutions.

Senior AI Engineer at GitLab focused on building internal AI-powered solutions to drive business outcomes across Sales, Marketing, and Customer Support. The role involves diagnosing business problems, designing and shipping AI solutions end-to-end, improving organizational flow, and integrating AI capabilities into existing systems. Emphasizes practical outcomes, measurable business value, and leveraging AI as a productivity multiplier.

Senior Backend Engineer responsible for building and improving backend systems for Wiki, Pages, Markdown, and text editors, with a focus on designing and integrating AI-powered capabilities like the planner agent and MCP integrations. The role involves architecting AI agents and MCP integrations that connect GitLab's GraphQL APIs with external AI platforms and tools, while also driving improvements in reliability and performance of existing systems. The engineer will mentor other engineers and collaborate across teams.

Staff Backend Engineer (Python) on the Duo Chat team, responsible for the backend architecture of GitLab Duo Chat. This role involves integrating and evolving LLM providers, improving observability and testing, and driving architectural decisions for a scalable AI-powered chat experience within the DevSecOps platform.

Staff Backend Engineer focused on integrating AI and agentic features into GitLab CI/CD workflows. The role involves shaping and scaling backend infrastructure, designing AI-powered features, defining success metrics for AI in CI, building observability for AI systems, and improving performance of CI systems. Requires strong Ruby on Rails, PostgreSQL, and experience with AI-powered backend features and observability.

Staff Forward Deployed Engineer focused on helping strategic enterprise customers adopt GitLab and the GitLab Duo Agent Platform in complex, regulated environments. The role involves deep technical discovery, designing adoption paths, building reusable solutions for AI-enabled workflows, and influencing product direction based on field needs. This role is customer-facing and involves hands-on engineering to solve adoption blockers and create durable technical assets.

This role focuses on helping strategic enterprise customers adopt GitLab and its AI capabilities, specifically the GitLab Duo Agent Platform. The engineer will guide technical discovery, design adoption paths, and build reusable solutions for complex, often regulated, environments. They will also contribute to upstream product and engineering decisions based on field needs, turning recurring customer issues into durable technical assets and influencing architecture patterns.

This role focuses on helping strategic enterprise customers adopt GitLab and its AI capabilities, specifically the GitLab Duo Agent Platform. The engineer will guide technical discovery, design adoption paths, and build reusable solutions for complex, often regulated, environments. They will also contribute to upstream product and engineering decisions based on field needs, turning recurring customer issues into durable technical assets and influencing architecture patterns.

Staff Forward Deployed Engineer role focused on helping enterprise customers adopt GitLab Duo Agent Platform in complex, regulated environments. This role involves deep technical discovery, designing adoption paths, and building reusable solutions for AI-enabled workflows, influencing product direction based on field needs.

This role focuses on helping enterprise customers adopt GitLab and the GitLab Duo Agent Platform, particularly in complex, regulated, or constrained environments. The engineer will guide technical discovery, design adoption paths, and build reusable solutions for AI-enabled workflows, including AI Gateway and model connectivity. They will also contribute code or design changes upstream when necessary and create durable technical assets to influence product direction.

This role focuses on applying AI to enhance infrastructure security within a DevSecOps platform. The Staff Infrastructure Security Engineer will set architectural patterns, lead security initiatives, conduct threat modeling, and define the team's approach to AI-assisted security engineering. The role requires expertise in cloud security, container orchestration, Infrastructure-as-Code, and hands-on experience with AI in security workflows.

This role focuses on engineering security improvements for the GitLab product, specifically building and maintaining tools to detect and prevent abuse on SaaS platforms. It involves predicting abuse patterns, building prevention systems, and improving agentic AI capabilities within abuse mitigation tools. While a strong software engineering background in Ruby/Rails is required, formal security engineering experience is not. The role also involves collaborating with peers, resolving automation gaps, and creating documentation.

Director of Enterprise Architecture & AI Intelligent Automation responsible for defining and governing how GitLab's internal systems connect, integrate, and evolve. This role will lead Enterprise Architecture, Integration, & RPA teams, setting architectural standards, governance frameworks, and strategic vision. The role involves shaping the long-term architecture, establishing an Architecture Review Board, rationalizing automation and integration, and clarifying when to use AI, RPA, or traditional integration. The goal is to reduce shadow IT and software sprawl, drive clear patterns for data flows, and ensure compliance with SOX and security requirements.

This role focuses on building AI-powered workflows and integrations within the Legal & Corporate Affairs team to automate legal tasks, improve efficiency, and enhance visibility. The Legal Engineer will translate legal requirements into technical solutions, own parts of the legal technology stack, and collaborate with internal AI teams to embed legal logic into company-wide tooling.

Staff Forward Deployed Engineer at GitLab focused on helping strategic customers adopt the GitLab Duo Agent Platform and AI-enabled workflows in complex enterprise environments. The role involves deep technical discovery, designing adoption paths, building reusable solutions, and influencing product direction based on field needs. It emphasizes working with AI tools and platforms within a DevSecOps context.

Senior Backend Engineer focused on building backend systems for an AI Governance product. This role involves implementing pipelines for AI audit events, access control for AI features, storage for AI agent artifacts, and services for an AI agent registry. The work is at the intersection of AI, governance, and enterprise backend engineering, supporting regulated organizations in adopting AI agents with confidence.

Intermediate Backend Engineer on the AI Governance team at GitLab, responsible for building a paid product for regulated enterprise organizations to audit, govern, and demonstrate compliance for AI agent usage within GitLab. The role involves implementing backend features for visibility and governance controls, working with Ruby on Rails and PostgreSQL, and collaborating with cross-functional teams in an all-remote environment.

Staff Backend Engineer on the GitLab Knowledge Graph team, responsible for designing, scaling, and operating a high-impact graph data service that underpins agents, analytics, and architecture-level features. The role involves building a distributed SDLC indexing system using ClickHouse, NATS JetStream, and the Data Insights Platform, and exposing secure graph queries and MCP tools for AI agents and product features. The engineer will own core parts of the system end-to-end, focusing on architecture, multi-tenant behavior, performance, and ease of consumption by other teams and agents. The role also emphasizes operational maturity, collaboration with AI teams, and applying AI-assisted development workflows.