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
- 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
#LI-KM8
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.
Skills Required
- Foundational understanding of AI and machine learning technologies, with experience leveraging, securing, or positioning AI-driven solutions
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience
- 10 or more years of software engineering experience
- Significant expertise in distributed systems, platform engineering, or machine learning infrastructure
- Experience building, deploying, and operating production-grade AI, machine learning, or LLM systems at scale
- Strong expertise in Python and systems languages such as Go, C++, Rust, or Java
- Hands-on experience with Docker, Kubernetes, and cloud-native deployment patterns
- Experience implementing AI safety, evaluation benchmarks, guardrails, and LLM observability frameworks
- Experience with RAG systems, vector databases, embedding pipelines, and retrieval tuning
- Experience with inference and serving frameworks such as vLLM, TensorRT-LLM, Triton, or Ray Serve
Zscaler Compensation & Benefits Highlights
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Healthcare Strength — Coverage is described as comprehensive across medical, dental, and vision, with mental‑health access and targeted programs for complex and chronic needs. Inclusive options span fertility, gender‑affirming care, and specialized support such as menopause and cancer‑care navigation.
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Parental & Family Support — Paid parental leave is outlined for all parents, with additional disability time for birthing parents and a ramp‑back period at full pay. Family‑building benefits and adoption assistance are also highlighted.
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Equity Value & Accessibility — Equity grants (RSUs) and a discounted stock purchase plan are positioned as meaningful components of total rewards. Feedback suggests these programs enhance overall compensation, particularly in eligible roles.
Zscaler Insights
What We Do
Zscaler accelerates digital transformation so our customers can be more agile, efficient, resilient, and secure. Our cloud native Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location.
Why Work With Us
Our impact comes from how we work—every day, in every decision, as one team. Our values and leadership principles are more than words; they're our operating system. They fuel a culture of execution where trust, transparency, and accountability help us deliver meaningful results for our customers, colleagues, and our company. www.zscaler.com/culture
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Zscaler Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
