Senior Backend Engineer, SSCS: AI Governance
Confirmed live in the last 24 hours
GitLab
Job Description
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. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software.
*Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. 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
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