Palo Alto Networks

Sr Staff Software Engineer

$154K–$249K

Office - USA - CA - Headquarters · No · Senior Staff · Full-time · Posted Oct 19, 2026

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Experience: 8+ years in Software Engineering, Cloud Engineering, SRE, or Cloud FinOps teams; 2+ years building software tools or AI/ML integrations for cloud resource management.
Visa sponsorship: No visa sponsorship; applicants requiring sponsorship, including new H-1B petitions or future sponsorship to maintain work authorization, are not considered. Applicants currently in OPT/CPT status are also not considered.

About the job

Build AI-driven, multi-cloud FinOps systems that analyze AI/ML workloads and automatically identify and execute cloud-cost savings.

What you'll do

Develop autonomous systems and AI agents to inspect, govern, and optimize AI/ML workloads and cloud infrastructure.
Automate GPU provisioning, model batching, cost checks, and savings workflows across cloud providers.
Build telemetry and predictive ML systems to measure unit economics and detect spending anomalies.

What they ask for

8+ years of experience in Software Engineering, Cloud Engineering, SRE, or Cloud FinOps teams, including 2+ years building software tools or AI/ML integrations for cloud resource management.
Strong software engineering fundamentals in Python, ReAct, and TypeScript/Node.js; practical experience with LLM APIs, vector databases, and agentic frameworks.
Hands-on FinOps API experience across AWS, GCP, and Azure; mastery of Terraform and Pulumi plus CI/CD engine experience.
Must be local to Bay area to be onsite; company is not considering applicants who require visa sponsorship or who are in OPT/CPT or other status requiring future sponsorship.

Nice to have

Experience with Kubernetes cost allocation tools such as Kubecost or OpenCost.
Proficiency with SQL, BigQuery, or Snowflake for processing billing exports.

Pay

$153,700.00 - $248,600.00/yr (USD, annual base salary)

Tools

AWS, Azure, GCP, LangChain, ADK, Python, ReAct, TypeScript/Node.js

AI focus

Build and deploy autonomous AI agents and predictive machine-learning systems to optimize AI/ML workloads, analyze telemetry, detect waste and anomalies, and automate cloud-cost savings.

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