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 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
Define engineering standards, architectural patterns, and best practices for building robust enterprise AI systems

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
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience
10+ years of software engineering experience, with significant expertise in distributed systems, platform engineering, or machine learning infrastructure
Proven experience building, deploying, and operating production-grade AI/ML or LLM systems at scale
Strong expertise in Python and systems languages such as Go, C++, Rust, or Java, alongside hands-on experience with Docker, Kubernetes, and cloud-native deployment patterns

What Will Make You Stand Out (Preferred Qualifications)

Hands-on experience implementing AI safety, evaluation benchmarks, guardrails, and observability frameworks for LLMs in enterprise environments
Strong experience in RAG systems, vector databases, embedding pipelines, and retrieval tuning
Experience with inference and serving frameworks such as vLLM, Tensor RT-LLM, Triton, Ray Serve, or equivalent

#LI-hybrid

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At Zscaler, we are committed to building a team that reflects the communities we serve and the customers we work with. We foster an inclusive environment that values all backgrounds and perspectives, emphasizing collaboration and belonging. Join us in our mission to make doing business seamless and secure.

Our Benefits program is one of the most important ways we support our employees. Zscaler proudly offers comprehensive and inclusive benefits to meet the diverse needs of our employees and their families throughout their life stages, including:

Various health plans
Time off plans for vacation and sick time
Parental leave options
Retirement options
Education reimbursement
In-office perks, and more!

Learn more about Zscaler's hybrid working model and benefits here.

By applying for this role, you adhere to applicable laws, regulations, and Zscaler policies, including those related to security and privacy standards and guidelines.

Zscaler is committed to providing equal employment opportunities to all individuals. We strive to create a workplace where employees are treated with respect and have the chance to succeed. All qualified applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy or related medical conditions), age, national origin, sexual orientation, gender identity or expression, genetic information, disability status, protected veteran status, or any other characteristic protected by federal, state, or local laws. See more information by clicking on the Know Your Rights: Workplace Discrimination is Illegal link.

Pay Transparency

Zscaler complies with all applicable federal, state, and local pay transparency rules.

Zscaler is committed to providing reasonable support (called accommodations or adjustments) in our recruiting processes for candidates who are differently abled, have long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support.