Key skills
AI/ML technologiesAI/ML platform product managementAI infrastructureDeveloper-facing platformsAgentic AILLM-based agent frameworksMulti-agent orchestrationAgent memory and tool useModel Context Protocol (MCP)AI observabilityAI loggingAI governanceAI complianceResponsible AI frameworksPlatform roadmap ownershipProduct architecture designLLM tool-use frameworksModel context communication layersUser experience designCybersecurity domain knowledgeGoAIMLLLMAgenticAgileProduct ManagementCommunicationCollaboration
About this role
Zscaler accelerates digital transformation to ensure our customers can be more agile, efficient, resilient, and secure. They are seeking a Principal Product Manager to own the shared foundation that empowers all SecOps product teams to build, deploy, and operate AI agents reliably and responsibly.
Responsibilities:
- Lead Product Discovery - Deeply understand the needs of internal teams (application PMs, engineering, automation) and end-user personas, conduct market research on the agentic AI landscape, and drive ideation for shared agent capabilities, infrastructure, and unified UX
- Define Product Vision and Roadmap - Own the vision and roadmap for the agentic platform — spanning agent runtimes, shared tooling, agent library, AI compliance, and unified agent UX — from discovery through launch and iteration
- Drive Day-to-Day Execution with Engineering - Partner with engineering and AI/ML teams to prioritize backlogs, clarify scope, and ensure high-quality delivery — enabling application teams to ship agents faster and more reliably
- Enable and Align Stakeholders - Collaborate with application PMs and go-to-market functions to ensure platform capabilities integrate seamlessly into product workflows and support RFP responses, pilots, and customer adoption
- Measure Success and Iterate - Define and track platform success metrics — including agent adoption, delivery velocity, and end-user engagement — and use data and feedback to continuously improve AI platform quality and value
Requirements:
- Foundational understanding of AI/ML technologies and experience leveraging, securing, or positioning AI-driven solutions to optimize outcomes within your functional domain
- AI/ML Platform or Infra Product Management — Proven experience owning shared developer-facing platforms, AI infrastructure, or internal tooling products; comfortable working in platform/horizontal roles rather than end-user feature work
- Agentic AI & LLM Ecosystem Fluency — Hands-on familiarity with LLM-based agent frameworks, multi-agent orchestration patterns, agent memory and tool use, and emerging standards like MCP (Model Context Protocol)
- AI Observability, Logging & Governance — Experience defining requirements for agent tracing, evaluation, audit logs, and guardrails — including AI compliance, safety policies, and responsible AI frameworks in an enterprise context
- Cross-Functional Platform Roadmap Ownership — Track record of managing a platform roadmap that serves other product and engineering teams as internal customers, including prioritization across competing use-case demands and driving alignment with engineering on shared services and tooling
- Experience designing scalable product architectures for multi-agent orchestration, advanced LLM tool-use frameworks, or standardized model context communication layers
- Bachelor's degree in Computer Science, Engineering, or a related field; a Master's or MBA is a plus
- UX & Product Design Collaboration for Complex Workflows — Experience owning or co-owning a unified user experience for a technical or multi-component product alongside cybersecurity domain knowledge to navigate domain constraints