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Zscaler is seeking an Applied AI Architect for People & Culture to lead the transformation of its HR function into an AI-native operation. Reporting to the AI Transformation Director in Global HR, you will design, deploy, and continuously improve high-impact AI agents using Gemini, Claude, and MCP integrations—owning the full lifecycle from prototype to hardened product.
Your core responsibilities include: designing and deploying AI agents that solve fundamental HR process challenges (not just automating broken workflows); pairing deeply with subject matter experts (compensation analysts, recruiters) to build domain-specific agents while transferring technical knowledge so they can independently maintain tools; redesigning workflows from the ground up to address root issues; operating deployed solutions as a true product owner by monitoring adoption and turning skeptics into sponsors; and partnering with the AI Center of Excellence and Forward Deployed Engineering to solve integration challenges and co-create governance standards.
You are a "figure-it-out" person who navigates ambiguity with ease and addresses fundamental process issues rather than bolting AI onto the current state. You are technically fluent with a proven portfolio of shipped, adopted GenAI agents—hands-on with skills, MCPs, data, automations, prompt design, and evals. You are a force multiplier who teaches as you work, measuring success by the new capabilities you leave behind in others. You champion adoption and change management, bringing stakeholders along to ensure deployments stick. You are deeply aware of risks associated with people data, building with care while defining the long-term playbook for an AI-native HR function.
Minimum qualifications: 6+ years in HR technology, people operations, solutions, or business transformation; demonstrated hands-on experience building AI agents or automations that changed how real work gets done; technical fluency to design agent architecture, work with MCPs and governance systems, and evaluate outputs at the system level; track record of taking solutions from problem identification through real adoption while upskilling others; highly autonomous and self-directed, comfortable operating as a senior individual contributor in a domain being invented in real time.
Preferred: rare intersection of engineering depth and HR practice; deep understanding of balancing cutting-edge agent building with practical realities and sensitivities of HR operations; drawn to early-stage, high-impact opportunities and eager to author the playbook for AI-native HR.
