Senior Backend Engineer, SSCS: AI Governance

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation.

More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact.

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Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025.

Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Senior Backend Engineer, AI Governance at GitLab, you will help build the backend systems behind a paid product for regulated enterprise organizations that need clear visibility, policy controls, and compliance evidence for AI use inside the software development lifecycle.

This role sits at the intersection of AI, governance, and enterprise backend engineering, where your work will help customers adopt AI agents with more confidence. You will contribute across the AI Governance product surface rather than focus on a single narrow area.

That includes backend work for audit event ingestion and export, role-based access control, governance features for the Model Context Protocol (MCP) registry, and storage systems for AI agent artifacts. You will work on technical problems with meaningful scope and complexity, partnering closely with the team on architecture and implementation in an async-first environment.

This is a good fit for someone who enjoys building reliable systems for enterprise use cases, designing for scale, and working in a space where product requirements are shaped by emerging AI regulations and customer governance needs. Your work will directly support organizations that need to manage AI usage with the same rigor they apply to security, compliance, and software delivery.

What you’ll do Implement and evolve the AI audit event pipeline, including event ingestion, schema normalization, storage design, partitioning, retention, and export capabilities. Implement access control for AI Governance features by integrating permissions for audit logs, policy configuration, and governance dashboards into GitLab's existing authorization model.

Contribute backend functionality for the AI agent artifact feature, supporting structured storage and retrieval of agent run metadata alongside existing CI/CD artifacts. Build backend services for the MCP registry, including tool metadata and enforcement controls that can restrict or block access when needed.

Design and optimize data models and queries for high-write, event-heavy systems using PostgreSQL and ClickHouse. Write and maintain solid RSpec and integration test coverage, while helping improve team test reliability practices.

Contribute to architecture decisions and deliver implementations with ownership, while working closely with partner teams in AI and Continuous Delivery. What you’ll bring Extensive experience building backend applications with Ruby on Rails in production environments.

Proficiency in Python and experience building backend services that support AI infrastructure, gateways, or adjacent product systems. Extensive experience with PostgreSQL and other data-intensive databases such as ClickHouse, including schema design, partitioning strategies, and efficient query patterns for event-heavy workloads.

Experience building REST or GraphQL APIs and designing backend systems for reliable storage, retrieval, and governance workflows. Solid understanding of authorization, access control, and enterprise governance concepts in web application architectures.

Familiarity with regulatory compliance, auditability, or enterprise governance requirements, and the ability to apply them in production systems. Clear written communication skills and comfort working effectively in a remote, async-first team.

Helpful experience includes audit trails, telemetry, event streaming, SIEM integrations, webhook delivery, enterprise retention requirements, AI agent infrastructure, large language models, the Model Context Protocol (MCP), or compliance, observability, and enterprise security products. About the team You'll join the AI Governance team within GitLab's Secure, Scale, and Compliance area.

We focus on helping organizations gain visibility into and govern AI usage inside GitLab. Our work spans two broad problem spaces: visibility, such as audit events, usage tracking, and observability, and policy controls, such as controls that help protect projects and meet compliance requirements.

We are building this team alongside a parallel AI Governance team, with both groups contributing to different parts of a fast-changing roadmap. You'll work with a distributed group of engineers and collaborate with adjacent AI and Continuous Delivery teams as we integrate governance capabilities more deeply into the platform.

It's an interesting team for engineers who want to work on emerging product challenges at the intersection of AI, compliance, and large-scale enterprise software. For more on how related teams work, see Team Handbook Page .

How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Home Office Support Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification.

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