Staff AI-Driven CloudOps Engineer

Palo Alto Networks; Santa Clara (CA); On-site; USD 124,000 - 202,000; Full time

Job summary

Palo Alto Networks is seeking an AI-native Staff Software Engineer for Cloud Ops to build intelligent cloud engines and autonomous orchestration across AWS, Azure, and GCP. You will design self-healing, AI-driven infrastructure and bridge deep systems engineering with LLM-powered workflows.

The role emphasizes multi-cloud architecture, Kubernetes management, and secure, observable deployments. A focus on collaboration with AI/ML teams enables scalable, high-availability cloud services.

Qualifications

• 6+ years of experience in Cloud Software Engineering, Site Reliability Engineering (SRE), or Distributed Systems Infrastructure.
• 2+ years of hands-on experience integrating AI tools, LLMs, or predictive analytics into deployment workflows, pipelines, or software platforms.
• Proven track record of architecting and operating large-scale, high-throughput distributed systems.
• A mindset that moves past \"how do I automate this task?\" to \"how do I build an autonomous system that solves this permanently?\"
• Ability to partner with Core AI/ML teams to bridge deployment and high-availability cloud infrastructure.

Responsibilities

• Architect and maintain scalable cloud systems across AWS, Azure, and GCP using Pulumi, AWS CDK, or Terraform.
• Design and implement AI-driven provisioning, auto-scaling, and self-healing workflows.
• Develop autonomous agents and utilities to orchestrate complex deployment pipelines and security checks.
• Embed security and observability into the deployment process using OpenTelemetry, Prometheus, and LLM-powered auditing.

Skills

Software Engineering

AI Orchestration

Multi-Cloud

Kubernetes

CI/CD

TypeScript/Node.js

Go

Python

LLM APIs

Tools

Pulumi

Terraform

AWS CDK

GitHub Actions

GitLab CI

OpenAI API

LangChain

Job description

Palo Alto Networks is seeking an AI-native Staff Software Engineer for Cloud Ops to build intelligent cloud engines and autonomous orchestration across AWS, Azure, and GCP. You will design self-healing, AI-driven infrastructure and bridge deep systems engineering with LLM-powered workflows.

The role emphasizes multi-cloud architecture, Kubernetes management, and secure, observable deployments. A focus on collaboration with AI/ML teams enables scalable, high-availability cloud services.