About this role
Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform.
We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler.
Role
We are looking for a Senior AI Business Process Analyst, Go-To-Market (GTM) to join our team in a Remote within the United States role, reporting to the Director, CRM & PRM Applications in the Information Technology Business Applications department. You will combine deep SaaS GTM domain knowledge with experience defining decision-grade signals for sellers—across both direct and partner/channel-led selling—and partner with engineering to bring them to life as AI agents. In this role, you will identify where reps, partner managers, and leaders need real-time signals, and work with engineering to build and prioritize the roadmap for how AI-generated signals power seller decisions across the business.
What You’ll Do (Role Expectations)
• Lead business process analysis and discovery sessions with Account Executives & Sales Management to understand the current state, then articulate the future state and where AI should help
• Turn ideas into actionable, AI-powered insights and recommendations by identifying where sellers and sales leadership lack clarity, context, or preparation, and map the current seller process to pinpoint where AI should help
• Assess feasibility before building with engineering, including required data inputs and quality, business logic, dependencies, fit within existing seller workflows, and success metrics
• Write, test, and refine prompts and output formats for AI-generated content such as meeting briefs and deal summaries, and evaluate every output by whether it helps a seller or manager decide faster or better, retiring or reworking what doesn’t improve outcomes such as win rate, forecast accuracy, or rep productivity
• Monitor AI solution performance and adoption, gather seller feedback, continuously optimize output quality, reliability, and business impact, and report results to leadership to guide prioritization and investment
Who You Are (Success Profile)