Jobs at GitLab

As Manager of Solutions Architects, lead a team delivering technical solutions, mentor staff, and drive customer adoption of GitLab while collaborating across departments to ensure customer success and team performance.

As an AI Transformation Owner at GitLab, you will shape AI strategies, improve workflows, and drive adoption of AI solutions in your organization, working closely with an AI Engineer.

Build and maintain backend features for Agent Observability across the GitLab monolith and AI gateway. Design and implement GraphQL/REST APIs, improve automated tests (RSpec), collaborate cross-functionally, troubleshoot production issues on Tier 2 on-call, and help shape responsible AI integration and platform architecture.

Lead product strategy connecting planning, source code management, and AI-assisted development. Define spec-driven workflows, collaborate with engineering/design across Plan, SCM, Code Review and AI, use customer insights and data to prioritize, and help teams ship high-quality features enabling human-in-the-loop and autonomous development.

Design and build a unified analytics instrumentation platform using Go, Kubernetes, ClickHouse, and NATS. Improve data emission, transit, and quality for usage and billing, provide incident response and root cause analysis, collaborate with product and data teams to drive adoption, make tradeoffs for reliability and performance, and mentor engineers through reviews and documentation.

Manage a cross-functional engineering team building GitLab Duo Chat's AI-powered features. Define requirements with product and UX, contribute to architecture for scalable agentic AI, drive delivery and roadmap execution, improve testing, observability, performance, and coach engineers to foster an inclusive, high-performing team.

The role involves implementing and maintaining enterprise applications using NetSuite and Claude tools, focusing on optimizing processes like Quote To Cash and Procure to Pay. Responsibilities include development, system integration, project management, and ensuring collaboration with business partners.

Lead end-to-end design for AI-powered developer tools at GitLab. Create flows, wireframes, prototypes, and high-fidelity interfaces for AI agents, chat, and code-assist features. Define success metrics, iterate with PMs and engineers, establish AI-specific design patterns in the design system, mentor other designers, and contribute to product strategy and research-informed decisions.

Lead design for cross-cutting platform experiences at GitLab, collaborating with cross-functional teams, mentoring designers, and contributing to the design system while incorporating user research.

Lead a team of senior product managers across CI, artifact management, CD, and observability to define an AI-native product vision for agent-driven software delivery. Align engineering and go-to-market partners, use telemetry and customer insight to prioritize roadmaps, drive migration and adoption paths, and model AI-native product management practices to accelerate commercial growth and platform coherence.

Design and implement authentication features across the Rails monolith and GATE, including token issuance/validation, token migration, passkeys/passwordless, SSO/SAML/OIDC/LDAP/SCIM support, cryptographic key management, vulnerability remediation, and performance optimization while shaping roadmap and engineering standards.

Lead product strategy for GitLab's engineering analytics and insights platform, define multi-horizon roadmap, partner with data and engineering teams to build pipelines, knowledge graph integrations, dashboards, and conversational AI experiences that turn engineering data into decision-ready intelligence for software leaders.

Lead technical direction of Professional Services engagements: design GitLab reference architectures, perform large-scale migrations using Congregate, deploy/configure GitLab with Terraform and Ansible, produce technical designs and delivery kits, mentor consultants, and ensure scalable, secure, and tested automation across cloud and on-prem environments.

Lead engineering strategy and execution for GitLab's growth and monetization platforms including self-service purchase, billing, usage metering, entitlements, quote-to-cash, integrations (Zuora, Salesforce), and API-first scalable architectures. Align cross-functional partners, ensure reliability, compliance (SOX), and apply AI/ML for predictive pricing and usage forecasting to support usage- and impact-based pricing.

Hire, onboard, and mentor outbound BDRs across AMER to drive pipeline and results. Coach performance, plan hiring/onboarding, collaborate with Sales, Events, Digital, Marketing, and Sales Development Ops to improve qualification processes and outbound messaging, and partner with regional sales leaders to develop key accounts.

Build, ship, and maintain backend features enabling AI agents to interact with GitLab. Design GraphQL/REST APIs, extend tests (RSpec), work with PostgreSQL, troubleshoot production issues, and collaborate cross-functionally to integrate AI tooling responsibly.

Ownership of backend features for Agentic Tools: design and implement GraphQL/REST APIs, build secure scalable Ruby on Rails services, improve RSpec automated tests, collaborate across product and AI teams, participate in Tier 2 on-call, and shape architecture for AI agent interactions with GitLab.

Own lifecycle communications strategy for prospects, build and optimize automated email journeys, execute campaigns end-to-end (copy, segmentation, QA, testing, launch), collaborate cross-functionally, use data to drive improvements in engagement and funnel progression, and act as the email marketing SME for best practices and deliverability.

The Principal Solutions Architect will lead technical architectures, drive AI-focused solutions, collaborate across teams, and mentor others to guide customers in maximizing GitLab’s DevSecOps platform's value.

The Distinguished Engineer will pioneer autonomous SDLC capabilities by integrating AI into software development workflows, driving productivity and innovation across teams. Responsibilities include defining technical vision, conducting experiments, mentoring engineers, and ensuring compliance and safety of AI systems.