Staff Software Engineer(Cloudops)

Our Mission

At Palo Alto Networks®, we’re united by a shared mission—to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you’re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you’re in the right place.

Who We Are

In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us!

We believe collaboration thrives in person. That’s why most of our teams work from the office full time, with flexibility when it’s needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes.

Job Summary

Staff Software Engineer Cloud Ops

As an **AI-Native Cloud Software Engineer**, you won't just manage environments; you will build the software engines, intelligent pipelines, and autonomous systems that power our cloud presence. We are shifting from rigid configuration management to AI-driven, self-healing software architectures.

You will design, develop, and optimize highly available, distributed cloud applications and infrastructure services across AWS, Azure, and GCP. Treating the entire cloud ecosystem as a programmable, AI-orchestrated software entity, you will bridge the gap between deep systems engineering, application development, and LLM-powered systems orchestration.

--- Key Responsibilities

• Multi-Cloud Generative IaC & Software-Defined Infrastructure: Architect and maintain scalable cloud systems across AWS, Azure, and GCP using Pulumi, AWS CDK, or Terraform. Integrate AI development workflows and custom LLM agents to accelerate safe infrastructure compilation, drift detection, and automated cross-cloud refactoring.

• Intelligent Automation & Agentic Workflows: Engineer custom software utilities, internal services, and autonomous agents using (TypeScript/Node.js, Go, or Python, alongside frameworks like LangChain or CrewAI) to orchestrate complex provisioning, predictive auto-scaling, and closed-loop self-healing systems.

• AI-Driven Cloud Governance & Economics: Leverage predictive machine learning models to analyze multi-cloud spend patterns, autonomously executing real-time resource-optimization strategies via API-driven software actions (e.g., dynamic spot-instance bidding, intelligent right-sizing across AWS, Azure, and GCP).

• Cognitive Observability & Infrastructure Security: Implement next-gen observability frameworks (OpenTelemetry, Prometheus) coupled with AI anomaly detection. Embed security directly into the deployment pipeline, utilizing LLMs to automatically audit Cloud IAM policies, scan for vulnerabilities, and generate contextual patches. Intelligent

• Container Orchestration: Manage production-grade Kubernetes clusters (EKS, AKS, GKE). Optimize resource allocation, cluster auto-scaling, and service meshes using AI-driven traffic routing and predictive capacity planning.

• Autonomous Incident Response: Act as a tier-3 software escalation engineer for complex distributed systems anomalies. Help design and train our internal "On-Call AI Agent" to ingest logs, perform automated Root Cause Analysis (RCA), and submit pre-validated Pull Requests to resolve underlying system defects.

Required Skills & Qualifications

Technical Expertise

• Software Engineering & AI Orchestration: Strong software engineering fundamentals in TypeScript (Node.js), Go, or Python. Experience interfacing with LLM APIs (OpenAI, Anthropic, Google Vertex AI, AWS Bedrock), vector databases, and prompt engineering for systems-level orchestration.

• Multi-Cloud & Containers: Deep proficiency in at least two major cloud platforms (AWS, Azure, GCP) with a strong architectural understanding of the third. Expert-level knowledge of Kubernetes (CKA preferred) and cloud-native networking.

• Next-Gen CI/CD: Experience building intelligent delivery pipelines using GitHub Actions or GitLab CI,