Staff Site Reliability Engineer (Production Engineer)- Federal

Zscaler•Short Hills, NJ

15h•$119,000 - $170,000•Hybrid

About The Position

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 160+ public exchanges globally and thousands of private exchanges 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 Staff Site Reliability Engineer (Production Engineer) to join our team. This is a hybrid role (onsite three days a week in San Jose, CA or another Zscaler office; remote can be considered for exceptional candidates) reporting to the Senior Manager, Site Reliability Engineering in the Zero Trust Exchange department. As a key member of the Zero Trust Exchange team, you will own the systems-level reliability and performance of Zscaler’s high-throughput bare-metal and cloud infrastructure processing tens of billions of daily transactions across a global, multi-region fleet. This is a software-first SRE role: you will write production-grade code and automation, drive the shift from reactive incident response, and bring engineering discipline to the systems-level work - OS, network and application debugging - that keeps the fleet operating safely at scale.

Requirements

US Citizenship is required (due to the nature of assigned customers)
Foundational understanding of AI/ML technologies and experience leveraging, securing, or positioning AI-driven solutions to optimize outcomes within your functional domain
5+ years of experience in Site Reliability Engineering, Production Engineering, or Systems Engineering operating high-scale, low-latency production platforms
Proven ability to write and debug executable code live (Python, Go, or Bash) covering core logic/data structures, along with hands-on experience writing Ansible playbooks/tasks for infrastructure automation
Deep knowledge of Linux OS internals and kernel troubleshooting (e.g., inodes, open file descriptors, process states, and analyzing df vs du storage discrepancies)
Comprehensive understanding of networking protocols and packet-level analysis, including DNS resolution workflows, TLS handshakes, TCP/IP mechanics, and packet captures via tcpdump

Nice To Haves

Hands-on experience operating and managing FreeBSD / BSD operating systems in production
Proven expertise running, scaling, and troubleshooting Kubernetes clusters in high-traffic, low-latency environments and workflow orchestration platforms (Temporal or similar)
Deep experience with Prometheus / OpenTelemetry ecosystems, or leveraging AI/ML frameworks/AIOps tools for automated root-cause analysis

Responsibilities

Maintain high availability across large-scale bare-metal Linux/BSD fleets, Kubernetes clusters, and custom routing stacks in partnership with Engineering and Networking teams
Lead full-cycle incident response by conducting cross-stack troubleshooting using low-level OS and network tools (strace, lsof, tcpdump, iostat, vmstat, gdb), maintain high availability across large-scale bare metal Linux /BSD fleets and Kubernetes clusters
Automate infrastructure lifecycle management, service provisioning, configuration workflows, and release deployments using Ansible, Python, and Go; quantify operational toil and convert recurring manual work into durable, version-controlled, testable automation — tracking reduction as an engineering outcome
Own end-to-end telemetry (metrics, logs, traces) using Prometheus and OpenTelemetry ecosystems; define and enforce SLOs/error budgets to reduce alert noise
Perform architectural reviews, OS/kernel upgrades, capacity and performance tuning, strict CI/CD validation prior to production rollouts; embed operability standards (telemetry, rollback safety, SLO readiness) into service design from the start