Principal Software Development Engineer

About Zscaler

Zscaler accelerates digital transformation to ensure our customers can be more agile, efficient, resilient, and secure. As an AI-forward enterprise, we are constantly pushing the envelope, leveraging the world’s largest security data lake to power our cloud-native Zero Trust Exchange platform. This innovation protects our customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location.

Here, impact in your role matters more than title and trust is built on results. We say, impact over activity. We seek innovators who actively use AI to amplify their impact and who thrive in an environment where we leverage intelligent systems to stay ahead of evolving threats. We believe in transparency and value constructive, honest debate—we’re focused on getting to the best ideas, faster. We build high-performing teams that can make an impact quickly and with high quality. To do this, we are building a culture of execution centered on customer obsession, collaboration, ownership, and accountability.

We value high-impact, high-accountability with a sense of urgency where you’re enabled to do your best work and embrace your potential. If you’re driven by purpose, thrive on solving complex challenges, and want to be part of the team that’s helping to secure the AI age, we invite you to bring your talents to Zscaler and help shape the future of cybersecurity.

Role

We are looking for a Principal Software Development Engineer to join our team. This is a Hybrid role, reporting to the Senior Director, Software Engineering in the ZPA department. You will lead the architecture, deployment, and evolution of large-scale Generative AI platforms and intelligent agent systems in production.

As a hands-on technical leader, you will design high-performance AI systems that are scalable, secure, observable, and production-ready, while building critical platform components and partnering across multidisciplinary teams to deliver reliable AI capabilities at scale.

What you’ll do (Role Expectations)

• Build and maintain MCP (Model Context Protocol) servers to standardize secure interactions between LLMs, agents, enterprise tools, APIs, databases, and local resources

• Design and deploy high-performance containerized Generative AI workloads in production using Docker, Kubernetes, model quantization, and KV-cache optimization to reduce latency and memory footprint