Staff Backend Engineer, Sscs: AI Governance

GitLab GitLab · Enterprise · India · Sec Engineering

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.

What you'd actually do

  1. Define and drive backend architecture for AI governance systems, including auditability, policy enforcement, and enterprise reporting capabilities, to improve governance coverage and enable reliable enterprise adoption.
  2. Design the AI audit event system, including event schema, pipelines, storage patterns, retention considerations, and export surfaces, to deliver reliable audit visibility and support customer reporting and compliance requirements.
  3. Build and guide the integration layer between the Duo Agent Platform and governance capabilities so agent actions can be observed and controlled at the right points in execution, reducing governance gaps across agent workflows.
  4. Guide technical design for tool and registry governance, including metadata models, permissions, and controls for managed tool usage, enabling safer, more consistent, and more governable tool access.
  5. Define backend foundations for a declarative policy framework that governs which agents and tools can be used under specific conditions, helping customers enforce governance requirements consistently across environments.

Skills

Required

  • Strong experience designing and operating backend systems at scale, especially in domains that require auditability, governance, or compliance.
  • Deep knowledge of authorization and access control patterns, such as role-based access control (RBAC), attribute-based access control (ABAC), and policy-as-code approaches.
  • Strong Ruby on Rails experience in production SaaS environments.
  • Strong Python experience, especially in systems related to AI services, orchestration layers, or service integrations.
  • Experience designing REST APIs and GraphQL APIs for internal or external platform use.
  • Familiarity with high-scale data and storage systems, including technologies such as Postgres and ClickHouse.
  • Proven experience guiding large, cross-team technical efforts in an async, RFC-driven engineering environment.
  • Communicate technical decisions clearly in writing and discussion, make sound tradeoffs during design and implementation, and influence technical direction across teams while collaborating and working effectively in a remote setting.

What the JD emphasized

  • governed at enterprise scale
  • auditability
  • policy-based governance
  • enterprise reporting
  • AI audit events
  • policy enforcement
  • tool governance
  • governance requirements

Other signals

  • AI Governance
  • auditability
  • policy enforcement
  • enterprise scale
  • agent workflows