Sr. Staff Software Engineer

Palo Alto Networks; California; Presencial; USD 154.000 - 249.000; Jornada completa

Descripción de la vacante

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

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

Python

ReAct

TypeScript/Node.js

LLM APIs

Vector databases

Agentic frameworks

FinOps

IaC (Terraform Pulumi)

CI/CD

Multi-cloud architecture

Herramientas

Terraform

Pulumi

CI/CD pipelines

Descripción del empleo

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

The Team Information Technology - Working at a high-tech cybersecurity company within Information Technology is a once-in-a-lifetime opportunity.

As an AI-Native Cloud FinOps Engineer, you will 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 heavily on AI/ML compute infrastructure like GPUs and LLM pipelines.

You will bridge the gap between deep systems engineering, machine learning, and multi-cloud financial operations to detect waste.

Treating cloud efficiency as a continuous software feature, you will leverage AI to convert potential optimizations into automated savings.

Key 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.

Qualifications

Qualifications Required

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.

Preferred Qualifications

Experience with Kubernetes cost allocation using tools like Kubecost or OpenCost.

Proficiency with big-data querying tools like SQL, BigQuery, or Snowflake to process 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.

Compensation Disclosure

The compensation offered for this position will depend on qualifications, experience, and work location.

For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/com‑missioned roles) is expected to be the annual range listed below.

The offered compensation may also include restricted stock units and a bonus.

A description of our employee benefits may be found here.

$153,700.00 - $248,600.00/yr

Our Commitment

We’re trailblazers that dream big, take risks, and challenge cybersecurity’s status quo.

It’s simple: we can’t accomplish our mission without diverse teams innovating, together.

We are committed to providing reasonable accommodations for all qualified individuals with a disability.

If you require assistance or accommodation due to a disability or special need, please contact us at [e-mail].

Palo Alto Networks is an equal opportunity employer.

We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation or other legally protected characteristics.

All your information will be kept confidential according to EEO guidelines.

Is role eligible for Immigration Sponsorship? No.