AI DevOps Engineer

Zscaler•San Jose, CA

20h•Hybrid

About The Position

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 an AI DevOps Engineer to join our team. This is a Remote within the United States (with a hybrid preference for San Jose, CA) role, reporting to the Manager, IT Cloud Operations in the Cloud Platform Engineering department. Our team builds and operates the internal cloud platform that powers Zscaler's product and corporate infrastructure across AWS, GCP, and Azure. In this role, you will design and ship automation that provisions cloud environments, enforces security baselines, and integrates AI-assisted tooling and agentic workflows to accelerate delivery.

Requirements

Demonstrated curiosity and active exploration of AI tools, with a proven history of integrating new technologies to enhance daily workflows and augment problem-solving
5+ years of experience building and operating multi-cloud infrastructure at scale across major cloud platforms
Hands-on expertise with Terraform, including module design, state management, and CI-driven workflows
Proficiency in scripting and automation using Python, Bash, or equivalent languages
Working knowledge of CI/CD pipeline design and Kubernetes operations
Understanding of identity federation, secrets management, and least-privilege security patterns

Nice To Haves

Experience with multi-account governance tooling such as AWS Control Tower, Organizations, SCPs, or RCPs
Experience with GitOps patterns and automated infrastructure lifecycle tooling such as Renovate, Dependabot, or ArgoCD
Experience with MLOps frameworks: kubeflow, ML flow, and model services like Bedrock, Sagemaker, Vertex AI, Gemini Enterprise

Responsibilities

Build and extend Day 1 automation, including infrastructure provisioning pipelines, account vending, golden repo templates, and CI/CD components
Build and extend Day 2 automation for lifecycle management, upgrade pipelines, dependency scanning, drift detection, and automated remediation workflows
Write and maintain Terraform modules, GitLab CI/CD components, and Python automation to establish the platform's paved road
Integrate AI and agentic tooling into operational workflows to reduce manual toil and increase operational consistency
Collaborate with Security, IAM, Network, and FinOps teams to translate cross-functional requirements into automated guardrails