Currently tracking 14 active AI roles, down 26% versus the prior 4 weeks. Primary focus: Agent · Engineering.
| Title | Stage | AI score |
|---|---|---|
| Staff Backend Engineer, SSCS: AI Governance 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. | AgentEval Gate | 7 |
| Senior Backend Engineer, SSCS: AI Governance 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. |
| Agent |
| 5 |
| Intermediate Backend Engineer, SSCS: AI Governance 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. | Agent | 5 |
| Staff Backend Engineer, Knowledge Graph (Rust) 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. | AgentData | 5 |