DevOps Engineer
United States of America
Full Time
2 hours ago
$160,000 - $220,000 USD
No H1B
Key skills
Google Vertex AILLMOpsAI automation pipelinesPythonGoData science principlesBigQueryGoogle Cloud PlatformGKECloud RunVPC Service ControlsAWSAzureGlobal load balancingCloud ArmorCloud interconnectsCross-cloud VPN architecturesTerraformAnsibleCI/CDGitOpsZero Trust IAMPolicy-as-code frameworksMetrics-driven canary deploymentsCloud certificationsAIArtificial IntelligenceMachine LearningOpenAIAnalyticsGCPGoogle CloudIAMVertex AILoad BalancingJiraConfluenceLeadershipProject ManagementCommunicationCollaborationZero Trust
About this role
Palo Alto Networks is dedicated to protecting our digital way of life through innovation and impact. They are seeking a high-level DevOps Platform Engineer to lead the evolution of their Multi-Cloud Platform, focusing on leveraging AI and Public Cloud Service Providers to create a cloud-native, intelligent ecosystem centered on Google Cloud Platform (GCP). This role offers opportunities for professional development while enhancing the team's understanding of cloud platform features and best practices.
Responsibilities:
- Architectural AI Integration: Design and implement AI-driven workflows using Google Vertex AI and LLMs to automate complex environment staging, documentation generation, and user support
- Multi-Cloud Ecosystem Leadership: Drive the strategy and management of production environments across GCP, AWS, and Azure, ensuring architectural consistency and cross-cloud resilience
- AIOps & Predictive Maintenance: Build self-healing infrastructure that utilizes machine learning to analyze telemetry data, predicting and remediating failures before they impact the user experience
- Advanced CI/CD & GitOps: Develop sophisticated pipelines that treat infrastructure as a living software product, incorporating automated security gates and AI-assisted code reviews
- Cloud-Native Governance: Oversee multi-tenant cloud environments with a focus on Zero Trust IAM, global security policy enforcement, and AI-optimized cost management
Requirements:
- Solid understanding of LLMOps and AI automation pipelines. You have a track record of integrating artificial intelligence APIs like Google Vertex AI or OpenAI directly into production DevOps workflows, managing complex prompt structures, and assisting with model adjustments
- High-level scripting capability for custom tools. You possess a background utilizing Python or Go to construct specialized automation agents, intelligent command-line interfaces, and custom operational tools
- Solid understanding of data science principles and analytics. You leverage cloud analytics frameworks like BigQuery to collect, structure, and refine infrastructure telemetry data for machine learning models
- Solid understanding of cloud administration across public providers. You bring high-level experience managing environments within Google Cloud Platform, specifically with GKE, Cloud Run, and VPC Service Controls, as well as managing enterprise workloads across AWS and Azure
- High-level networking and infrastructure design skills. Your experience covers a strong grasp of global load balancing configurations, Cloud Armor, cloud interconnects, and cross-cloud VPN architectures to ensure platform stability and security
- Solid understanding of Infrastructure as Code frameworks. You are proficient in leveraging automation tools such as Terraform or Ansible to build, maintain, and manage scalable cloud infrastructure setups
- High-level diagnostic and structural problem-solving abilities. You bring a strong capacity for deep-stack troubleshooting across complex environments to identify systemic platform issues and rapidly establish operational guardrails
- Solid communication and cross-functional collaboration skills. You are experienced at translating technical platform metrics into strategic value for leadership, leading formal root-cause analyses, and documenting designs into clear Standard Operating Procedures, alongside an understanding of industry-standard project management frameworks to utilize tools like Jira and Confluence for tracking technical tasks and prioritizing platform development effectively
- Plus factors for this role include experience integrating advanced progressive delivery models, such as metrics-driven canary deployments, natively within container orchestration clusters
- Plus factors for this role include a background in developing policy-as-code frameworks to implement zero-trust compliance standards without introducing development friction
- Plus factors for this role include relevant industry cloud certifications across GCP, AWS, or Azure, or specialized automation designations