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Zscaler is seeking a Principal AI Product Manager to define the vision, strategy, and roadmap for the Customer Success AI product portfolio. Reporting to the Director of Customer Success Intelligence & Automation, you will own strategic AI investments that augment employees, improve productivity, and deliver measurable business value across the global Customer Success organization.
In this role, you will define long-term vision and strategy for the Customer Success AI product portfolio, aligned to business priorities and operational goals. You'll identify and prioritize high-impact opportunities to apply AI across internal Customer Success workflows, including productivity, knowledge access, decision support, workflow automation, and operational intelligence. You will manage the AI product portfolio across incubation, pilot, production, scale, and optimization phases, leading products end-to-end from concept through launch, adoption, measurement, and lifecycle management.
You'll partner closely with Customer Success leaders, internal users, Engineering, UX, Data, AI Platform, and IT teams to translate pain points and complex workflows into intuitive, scalable AI-native products. You'll drive prioritization and tradeoff decisions across the portfolio by balancing user value, business impact, technical feasibility, risk, governance, and platform reuse.
Zscaler is an AI-forward enterprise leveraging the world's largest security data lake to power its cloud-native Zero Trust Exchange platform. The company culture emphasizes impact over activity, customer obsession, collaboration, ownership, and accountability. You'll thrive in ambiguity, act like an owner, remain customer-obsessed, collaborate at high trust, and think at scale.
Required qualifications: 10+ years of product management experience delivering enterprise software, SaaS products, or internal enterprise platforms, with 3+ years leading AI-powered, Generative AI, intelligent automation, or workflow intelligence products. You need a proven track record of defining long-term product strategy and managing complex product portfolios or interconnected product areas. Strong understanding of enterprise AI concepts and architectures, including LLMs, AI agents, RAG, prompt engineering, and evaluation approaches is essential. Foundational understanding of AI/ML technologies and experience leveraging, securing, or positioning AI-driven solutions to optimize outcomes within your functional domain is required.
