Principal Software Development Engineer - Agentic Systems

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 Principal Software Development Engineer - Agentic Systems to join our team. This is a hybrid role based in Bangalore, reporting to the Director, Software Development Engineering in the Exposure Management & Security Operations department. In this role, you will lead the architecture and delivery of large-scale AI/ML infrastructure and production pipelines, mentor team members, and drive strategic technical initiatives across the organization. You bring a deep understanding of building and operating distributed AI systems at scale and translating business challenges into reliable, production-grade AI platforms. What you’ll do (Role Expectations) Lead the architecture and development of scalable AI/ML infrastructure, LLM serving platforms, and agentic workflows tailored for cloud-scale cybersecurity use cases Architect reusable platform foundations—including networking, security, authentication, and monitoring—to standardize and secure enterprise AI/ML services Define and implement system observability, evaluation, and reliability frameworks to ensure optimal performance and stability of AI systems in production Drive cross-functional architectural initiatives in collaboration with product, security, and operations teams to deliver production-grade AI solutions aligned with business goals Provide technical leadership and mentorship on distributed systems design while translating complex architectures to non-technical stakeholders to foster alignment across the organization Who You Are (Success Profile) You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful. You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution. You are a problem-solver. You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact. You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust. You are a learner. You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose. What We’re Looking for (Minimum Qualifications) Foundational understanding of AI/ML technologies and experience leveraging, securing, or positioning AI-driven solutions to optimize outcomes within your functional domain Proven experience designing and operating large-scale, low-latency distributed systems, with deep expertise in availability, fault tolerance, consistency, and cloud-native microservices (AWS preferrable, GCP, or Azure) Expertise in LLMs and production AI/ML infrastructure, including orchestration frameworks, inference systems, and full-lifecycle pipeline operations Demonstrated track record of cross-organizational technical leadership, driving architectural decisions, mentoring teams, and shipping production-grade services Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, backed by a solid foundation in core computer science principles What Will Make You Stand Out (Preferred Qualifications) Demonstrate a proven ability to leverage AI technologies and workflows to drive measurable operational efficiency Proven track record with LLM observability, explainabi