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Salary: USD 117,250 - 167,500 / annual
Zscaler is seeking an AI Solutions Engineer to lead the transformation of its People & Culture function into an AI-native organization. This hybrid role (in-office Tuesday–Thursday) is based in Santa Clara, CA or Bellevue, WA and reports to the AI Transformation Director in Global People & Culture.
You will design, deploy, and continuously improve high-impact AI agents using Gemini agent builder, Claude, Codex, and MCP integrations, owning the full maturity path from prototype to hardened, governed product. You'll pair deeply with subject matter experts—compensation analysts, recruiters, and others—to build domain-specific agents while transferring your technical expertise so they can independently maintain and evolve their own tools.
A core responsibility is redesigning workflows from the ground up to solve fundamental process issues rather than simply automating broken systems. You'll operate as a true product owner, monitoring adoption, diagnosing failures, and guiding stakeholders from skepticism to sponsorship. You'll also partner closely with the AI Center of Excellence and Forward Deployed Engineering team to tackle hard technical integration challenges and co-create mature governance standards.
This role sits at the intersection of builder, teacher, and change agent. You'll measure success not just by shipped agents but by the new capabilities you leave behind in others and the real-world adoption you drive. You'll be deeply aware of risks associated with people data, building with care while defining the long-term playbook for an AI-native HR function.
Zscaler (NASDAQ: ZS) is a leader in zero-trust security, protecting thousands of customers through its SASE-based Zero Trust Exchange platform distributed across 200+ global data centers. The company is committed to building an AI-native enterprise where human potential is amplified by machine intelligence.
REQUIREMENTS:
- Demonstrated hands-on experience building AI agents, automations, or tools that changed how real work gets done
- Technical fluency sufficient to design agent architecture and instructions, work with MCPs and governance systems, and evaluate outputs at the system level without needing engineering handholding
- Track record of taking solutions from problem identification through real adoption while simultaneously upskilling others through training, enablement, or sustained co-working
- Highly autonomous, self-directed, and comfortable operating as a senior individual contributor in a domain being invented in real time
PREFERRED:
- Rare intersection of engineering depth and HR practice, ensuring technically correct agents that the field actually adopts
- Deep understanding of balancing cutting-edge agent building with practical realities, risks, and sensitivities of HR operations
- Drawn to early-stage, high-impact opportunities and eager to be a primary author of the playbook for AI-native HR
