GitLab
Senior
Own GitLab's AI Control Plane — governance, policy, and audit for agentic AI at enterprise scale
GitLab is hiring a Senior PM to own the AI Control Plane and foundational agentic-AI platform services (Flow Execution Engine, Constraint & Policy Store, Audit Log Service) that let enterprise platform teams safely govern agent activity. This interview probes platform/governance PM experience in B2B SaaS, fluency in agentic AI concepts (harnesses, MCP, agent identity, session lifecycle), and working knowledge of compliance frameworks (EU AI Act, ISO 42001, SOC 2, HIPAA) mapped to real product capabilities.
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What this interview tests
- Platform/governance product management in B2B SaaS
- Agentic AI platform concepts (MCP, agent identity, session lifecycle, guardrails)
- Enterprise compliance frameworks mapped to product requirements
- Competitive analysis of AI agent execution platforms and LLM providers
- Balancing near-term delivery vs long-term platform architecture
Common question themes
Describe a foundational/platform service you shipped with downstream integration points, not just a feature
How would you design guardrails and audit evidence for agentic AI activity at enterprise scale
Walk through mapping a compliance framework (e.g., EU AI Act, SOC 2) to concrete product capabilities
How do you make architectural tradeoffs (e.g., build vs adopt a policy engine) under ambiguity
Competitive positioning: how would you differentiate an AI control plane against other agent execution platforms
Tell me about driving product discovery directly with a top enterprise customer
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