Senior AI/FinOps Cloud Engineer - Multi-Cloud Optimizer

Palo Alto Networks; California; On-site; USD 154,000 - 249,000; Full time

Job summary

Palo Alto Networks is seeking an AI-Native Cloud FinOps Engineer in the Bay Area to design autonomous optimization pipelines for cloud spend across AWS, Azure, and GCP. You will focus on AI/ML compute, GPUs, and LLM pipelines, pushing from passive monitoring to self-optimizing architectures.

This role bridges systems engineering, machine learning, and financial operations to cut waste. You will build closed-loop automation, write IaC pipelines, and deploy predictive models to continually improve

Qualifications

• Minimum 8+ years of experience in Software Engineering, Cloud Engineering, SRE, or Cloud FinOps teams.
• 2+ years of hands-on experience building software tools or AI/ML integrations for cloud resource management.
• Strong software engineering fundamentals in Python, ReAct, and TypeScript/Node.js.
• Practical experience interfacing with LLM APIs, vector databases, and agentic frameworks.
• Deep understanding of the architectural and financial cost drivers of AI/ML workloads.
• Hands-on programmatic experience interacting with FinOps APIs across AWS, GCP, and Azure.
• Mastery of IaC tools like Terraform and Pulumi, combined with CI/CD engine experience.
• Proven track record of architecting and maintaining closed-loop automation tools in multi-cloud environments.
• Must be local to Bay area to be onsite.

Responsibilities

• Engineer autonomous systems using LangChain, ADK to inspect, govern, and optimize high-cost AI/ML workloads.
• Programmatically manage GPU cluster provisioning, optimize model batching, and track per-token unit economics.
• Write closed-loop software systems that automatically convert detected optimization opportunities into executed savings across clouds.
• Build infrastructure-as-code pipelines using Terraform and Pulumi embedded with real-time cost-compilation checks.
• Train and deploy predictive machine learning models to analyze real-time usage telemetry and detect spend anomalies.
• Lead the technical evolution of our FinOps maturity curve by building telemetry platforms to measure unit economics.
• Design internal AI agents that continuously analyze infrastructure state, detect waste, and submit pre-validated Pull Requests.

Skills

Python

ReAct

TypeScript/Node.js

LLM APIs

Vector databases

Agentic frameworks

FinOps

IaC (Terraform Pulumi)

CI/CD

Multi-cloud architecture

Tools

Terraform

Pulumi

CI/CD pipelines

Job description

Palo Alto Networks is seeking an AI-Native Cloud FinOps Engineer in the Bay Area to design autonomous optimization pipelines for cloud spend across AWS, Azure, and GCP. You will focus on AI/ML compute, GPUs, and LLM pipelines, pushing from passive monitoring to self-optimizing architectures.

This role bridges systems engineering, machine learning, and financial operations to cut waste. You will build closed-loop automation, write IaC pipelines, and deploy predictive models to continually improve