AI‑Native FinOps Engineer: Cloud Cost Optimizer

Jobs Paloaltonetworks; California; On-site; USD 145,000 - 236,000; Full time

Job summary

Palo Alto Networks in the Bay Area seeks an AI-Native Cloud FinOps Engineer to build intelligent pipelines and autonomous optimization systems that control our cloud spend across AWS, Azure, and GCP. Shifting from passive financial monitoring to AI-driven, self-optimizing architectures, you will focus on AI/ML compute infrastructure like GPUs and LLM pipelines.

You will bridge deep systems engineering, machine learning, and multi-cloud financial operations to detect waste and convert

Qualifications

• 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 Python, ReAct, and TypeScript/Node.js fundamentals.
• 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

AI/ML integrations

Cloud FinOps concepts

Multi-cloud cost management

Tools

Terraform

Pulumi

LangChain

CI/CD tooling

Vector databases

Job description

Palo Alto Networks in the Bay Area seeks an AI-Native Cloud FinOps Engineer to build intelligent pipelines and autonomous optimization systems that control our cloud spend across AWS, Azure, and GCP. Shifting from passive financial monitoring to AI-driven, self-optimizing architectures, you will focus on AI/ML compute infrastructure like GPUs and LLM pipelines.

You will bridge deep systems engineering, machine learning, and multi-cloud financial operations to detect waste and convert