Sr. Staff Software Engineer

Palo Alto Networks • Office - USA - CA - Headquarters, CA

5d • $153,700 - $248,600 • Onsite

About The Position

As an AI-Native Cloud FinOps Engineer on the Information Technology team, you will build intelligent pipelines and autonomous optimization systems to control cloud spending across AWS, Azure, and GCP. The role shifts cloud financial operations from passive monitoring to AI-driven, self-optimizing architectures, with a strong focus on AI/ML compute infrastructure such as GPUs and LLM pipelines. You will combine systems engineering, machine learning, and multi-cloud financial operations to detect waste and automate savings.

Requirements

• At least 8 years of experience in Software Engineering, Cloud Engineering, SRE, or Cloud FinOps teams.
• At least 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 infrastructure-as-code tools such as Terraform and Pulumi, combined with CI/CD engine experience.
• Proven track record architecting and maintaining closed-loop automation tools in multi-cloud environments.
• Must be local to the Bay Area to work onsite.

Nice To Haves

• Experience with Kubernetes cost allocation using tools such as Kubecost or OpenCost.
• Proficiency with big-data querying tools such as SQL, BigQuery, or Snowflake for processing billing exports.
• Ability to partner with AI/ML Engineers, Product Leaders, and FP&A to align infrastructure strategies with financial goals.
• A software-first, agentic problem-solving mindset focused on writing self-healing systems.

Responsibilities

• Engineer autonomous systems using LangChain and 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.
• Develop closed-loop software systems that convert detected optimization opportunities into executed savings across clouds.
• Build infrastructure-as-code pipelines using Terraform and Pulumi with real-time cost-compilation checks.
• Train and deploy predictive machine learning models to analyze real-time usage telemetry and detect spending anomalies.
• Lead the technical evolution of FinOps maturity 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.

Benefits

• Compensation may include restricted stock units and a bonus.
• The job description refers candidates to a benefits description but does not enumerate specific benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed