Principal AI Security Specialist

Principal AI Security Specialist

About the Role

Zscaler is seeking an experienced AI Security Specialist to help customers securely adopt and operationalize AI across the enterprise. This role is designed for a customer-facing technical expert who combines the consultative strengths of a Solutions Engineer / Solutions Consultant with deep expertise in AI, GenAI architectures, and AI security.

The AI Security Specialist will partner closely with Sales, Solutions Engineering, Product, and customers to configure, demonstrate, and position Zscaler’s AI security solutions. This individual will serve as a trusted advisor on secure AI adoption, helping customers understand how to protect data, enforce policy, reduce risk, and enable safe use of AI technologies across users, applications, and workflows.

This is a highly strategic, technical, and field-facing role for someone who can engage in executive conversations, lead architecture discussions, deliver compelling demos, and support technical validation for complex enterprise opportunities.

What You’ll Do

• Partner with account teams and core Solutions Engineering teams to drive the technical strategy for AI Security-related opportunities.
• Engage customers in discovery around AI initiatives, GenAI use cases, enterprise architecture, security requirements, and adoption challenges.
• Configure and deliver compelling demos of Zscaler’s AI security solutions, tailored to customer priorities and business outcomes.
• Support proofs of concept, proofs of value, and technical evaluations for strategic AI-related opportunities.
• Advise customers on how to securely enable AI usage across the enterprise, including data protection, policy enforcement, user access, governance, and risk mitigation.
• Translate complex AI and security concepts into clear, actionable value for technical, security, and executive stakeholders.
• Serve as a subject matter expert on modern AI technologies, including large language models (LLM), retrieval-augmented generation (RAG), agents, prompt workflows, model usage patterns, and emerging enterprise AI architectures.
• Help customers understand the security implications of enterprise AI adoption, including sensitive data exposure, unsanctioned AI usage, governance gaps, and operational risk.
• Collaborate with Product and Engineering to provide field feedback, influence roadmap priorities, and improve product positioning based on customer needs.
• Develop reusable demos, technical assets, competitive positioning, and enablement content to help scale Zscaler’s AI field motion.
• Enable internal teams on AI trends, AI security use cases, market messaging, and customer objections.
• Represent Zscaler in executive briefings, customer workshops, webinars, and industry events related to AI security and secure AI transformation.

What We’re Looking For

• 5+ years of experience in a customer-facing technical role such as Sales Engineering, Solutions Consulting, Solutions Architecture, Customer Engineering, or Technical Advisory.
• Deep understanding of modern AI and GenAI technologies, including:
• Large language models (LLMs)
• Retrieval-augmented generation (RAG)
• Agents, MCP and orchestration patterns
• Prompt workflows
• Model usage considerations, safety, and governance concepts
• Experience configuring, demonstrating, and presenting technical solutions in complex enterprise sales cycles.
• Strong ability to connect technical capabilities to business value, security outcomes, and customer priorities.
• Strong presentation, demo, and communication skills, with the ability to engage architects, practitioners, security leaders, and executives.
• Familiarity with enterprise architecture, cloud environments, APIs, application workflows, and integration patterns.
• Strong understanding of cybersecurity principles, with experience in one or more areas such as:
• cloud security
• data security
• zero trust architecture
• secure access
• governance and policy controls
• Ability to work cross-functionally with Sales, Solutions Engineering, Product, Engineering, Marketing, and other go-to-market teams.
• Comfort operating in a fast-moving market where AI technologies, buyer expectations, and competitive positioning continue to evolve.

Preferred Qualifications

• Experience in AI security, secure AI adoption, model governance, or AI-related risk management.
• Experience helping enterprises evaluate or deploy AI technologies in production environments.
• Hands-on experience building prototypes, demo environments, or lightweight AI applications.
• Hands on experience with deploying infrastructure in public cloud
• Familiarity with enterprise concerns around AI usage, including data leakage, policy violations, compliance, third-party AI tools, and governance.
• Experience supporting strategic accounts and complex technical buying cycles.
• Background in Python, APIs, scripting, or solution prototyping.
• Experience creating reusable field assets such as demo content, reference architectures, technical workshops, and playbooks.
• Familiarity with security platforms, cloud-native architecture, and modern SaaS security models.

Success in This Role Looks Like

• You become a trusted advisor to customers on both AI innovation and AI risk reduction.
• You help customers understand how Zscaler enables secure, scalable adoption of AI across the enterprise.
• You deliver high-impact demos and technical engagements that connect Zscaler’s capabilities to real customer priorities.
• You improve technical win rates for AI-related opportunities through strong discovery, positioning, and technical validation.
• You help the field scale through reusable assets, crisp messaging, and practical AI security guidance.
• You provide actionable customer insight that sharpens product strategy and go-to-market execution.

Why This Role Matters

Enterprises are rapidly adopting AI, but they are doing so in an environment filled with security, governance, and data protection concerns. Zscaler is uniquely positioned to help customers enable AI safely through zero trust principles, secure access, policy enforcement, and protection of sensitive data.

The AI Security Specialist plays a critical role in that mission by helping customers move from AI experimentation to secure, enterprise-wide adoption with confidence.

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