Zscaler
Staff Software Development Engineer
$152K–$190K
Santa Clara, California, USA · Staff · Full-time · Posted Oct 29, 2026
- Experience
- 5+ years of software engineering experience; significant large-scale distributed systems and backend platform services experience required.
About the job
Leads architecture and delivery of scalable, resilient, secure control plane and platform services for the Zero Trust Exchange, while guiding cross-team technical strategy and execution.
What you'll do
- Design and deliver large-scale control plane and platform services, improving scalability, availability, security, and operational excellence.
- Lead cross-team technical initiatives, align stakeholders on architecture and execution, and resolve reliability, performance, and architectural issues.
- Set engineering standards through reviews and mentorship; apply emerging technologies, including Agentic AI and AI-assisted workflows, where appropriate.
What they ask for
- 5+ years of software engineering experience, including significant experience designing and building large-scale distributed systems and backend platform services.
- Deep expertise in system design, microservices architecture, API design, data modeling, and operating highly available, fault-tolerant production services.
- Strong proficiency in one or more modern programming languages such as Java, Go, or Python, with a record of delivering production-grade software.
- Experience leading complex technical initiatives across teams, plus strong understanding of cloud-native technologies, observability, reliability engineering, and secure software development practices.
Nice to have
- Experience applying AI-forward engineering practices, such as developer copilots, intelligent automation, AI-assisted incident analysis, or ML/LLM-powered platform capabilities.
- Experience building mission-critical platform systems in SaaS or cybersecurity, with Kubernetes, PAM, or IGA; mentoring senior engineers is also valued.
Pay
$152,000 — $190,000 USD base salary
Tools
Java, Go, Python, Kubernetes, PAM, IGA, ML/LLM
AI focus
Explore and integrate AI tools into workflows; apply Agentic AI and AI-assisted engineering where appropriate. Preferred examples include developer copilots, intelligent automation, AI-assisted incident analysis, and ML/LLM-powered platform capabilities.
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