Staff Software Development Engineer - AI Engineer

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 an AI Engineer to join our team. This is a Hybrid role, reporting to the Engineering Manager in the Product Operations department. We are seeking a hands-on AI Engineer to help scale the agentic layer of our AI Native - Product Operations Platform. In this role, you will design and build production-grade AI systems, reusable platform capabilities, and the engineering harnesses required to safely develop, evaluate, debug, and operate AI workflows at scale. As a pragmatic builder who understands modern AI systems in practice, you will translate ambiguous business needs into scalable technical solutions in a high-velocity environment. What you’ll do (Role Expectations) Build and scale the agentic layer of the AI Native - Product Operations Platform by designing production-grade AI systems, reusable platform capabilities, and reliable execution patterns Develop Agentic AI capabilities by applying practical knowledge of RAG architectures, embeddings, vector retrieval, agent orchestration, and workflow state management Design and implement AI engineering harnesses for prompt testing, agent debugging, workflow replay, evaluation, regression testing, tracing, and controlled experimentation Build and maintain graph-based agent workflows, including multi-step reasoning flows, tool-calling paths, branching logic, human-in-the-loop checkpoints, and stateful execution patterns Implement standards, patterns, and guardrails to ensure AI development on the platform remains scalable, reliable, observable, and cohesive Who You Are (Success Profile) You are a pragmatic builder with a passion for rolling up your sleeves to create, iterate, and ship production-grade software. You thrive in ambiguity and fast-paced environments, maintaining focus and execution velocity amidst rapid change. You act like an owner, bringing deep accountability, a strong bias for action,…