Principal AI Product Manager
New
Z
ZscalerCybersecurity
Remote - USAFull-TimePrincipal
Salary171,500 - 245,000 USD per year
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Job Details
- Experience
- 10+ years of product management experience; 3+ years leading AI-powered, Generative AI, intelligent automation, or workflow intelligence products
- Required Skills
- Artificial IntelligenceProduct ManagementSaaSPrompt EngineeringGenerative AI
Requirements
- 10+ years of product management experience delivering enterprise software, SaaS products, or internal enterprise platforms.
- 3+ years leading AI-powered, Generative AI, intelligent automation, or workflow intelligence products.
- Foundational understanding of AI/ML technologies and experience leveraging, securing, or positioning AI-driven solutions.
- Strong understanding of enterprise AI concepts and architectures, including LLMs, AI agents, RAG, prompt engineering, evaluation approaches, and agentic workflows.
- Proven track record of defining long-term product strategy and managing complex product portfolios or interconnected product areas.
- Experience building workflow applications, employee productivity solutions, or internal enterprise products.
- Data-driven approach to defining KPIs, measuring adoption and business outcomes, and guiding prioritization.
- Exceptional product judgment, communication, leadership, and stakeholder management skills.
- Experience working cross-functionally across Engineering, Design, Data, Platform, and business teams.
Responsibilities
- Define the long-term vision, strategy, and roadmap for the Customer Success AI product portfolio, aligned to business priorities and operational goals.
- 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.
- Manage the AI product portfolio across incubation, pilot, production, scale, and optimization, leading products end to end from concept through launch, adoption, measurement, and lifecycle management.
- Partner closely with Customer Success leaders, internal users, Engineering, UX, Data, AI Platform, and IT to translate pain points and complex workflows into intuitive, scalable AI-native products.
- Drive prioritization and tradeoff decisions across the portfolio by balancing user value, business impact, technical feasibility, risk, governance, and platform reuse.
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