Key skills

Multi-cloud InfrastructureTerraformPythonBashCI/CD Pipeline DesignKubernetes OperationsIdentity FederationSecrets ManagementLeast-Privilege SecurityAWS Control TowerGitOpsArgoCDAIMLGeminiAgenticMLOpsKubeflowAWSAzureGCPKubernetesGitLab CIIAMSageMakerBedrockVertex AIGitLabCI/CDCloud SecurityZero Trust

About this role

Zscaler is a cloud security company that provides a Zero Trust Exchange platform to protect customers from cyberattacks and data loss. The AI DevOps Engineer will design and operate automation for multi-cloud environments across AWS, GCP, and Azure, integrating AI-assisted tooling and agentic workflows to improve delivery and operational consistency.

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

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
- 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