Jobs and Careers

Principal AI Tooling Engineer

Santa Clara, United Statesfull_timeVerifiedPosted 2 Apr 2026

💰 $237,500/yr($147,000/yr – $237,500/yr)

About the role

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

As a Principal Software Automation/Test Engineer, you'll play a critical role in our mission to secure the world’s digital transformation. Your work will directly impact the quality and reliability of the solutions that protect global enterprises every day. If you're passionate about driving quality at scale and want to be part of a team that's leading the charge in cloud security innovation, we want to hear from you.

Key Responsibilities

Architect next-gen platforms and comprehensive strategies for complex, large-scale systems.
Leverage AI to design intelligent tools that enhance testing efficiency, code quality, and productivity across the organization.
Integrate LLM-powered assistants and agentic workflows to automate repetitive tasks like test case creation, log analysis, and code review triage.
Evaluate and adopt technologies such as Retrieval-Augmented Generation (RAG) and fine-tuned models to push the boundaries of engineering automation.
Define best practices for responsible AI usage, including hallucination mitigation and human-in-the-loop review processes.
Design and implement internal tools, SDKs, and frameworks to boost engineering velocity and productivity.
Build robust automation frameworks equipped with detailed reporting, observability, and seamless CI/CD integration.
Manage complex testbeds and infrastructure-as-code solutions to support varied development and testing scenarios.
Develop AI-driven defect prediction and root cause analysis tools to accelerate the QA lifecycle.
Provide insights into engineering efficiency and tooling gaps to influence the development of cutting-edge solutions.
Guide root cause analysis of complex tooling failures and infrastructure incidents during and after releases.
Mentor junior and mid-level engineers, fostering a culture of ownership and engineering excellence.
Actively participate in the hiring process and technical interviews to help build a world-class tools engineering organization.

Qualifications

9+ years in software tooling or infrastructure engineering within large-scale enterprises or high-growth startups.
Strong programming skills in Python.
Proven experience leveraging AI/ML technologies (LLMs, agentic frameworks, prompt engineering) to build intelligent engineering tools.
Deep understanding of public cloud platforms (AWS, GCP, Azure) and building tools that leverage cloud-native services.
Demonstrated experience designing complex tooling frameworks from scratch with a focus on scalability and extensibility.
Proficiency in integrating technologies such as Pytest, Selenium, Playwright, Terraform, Docker, and Kubernetes.
Strong troubleshooting skills and experience supporting tooling for distributed systems and SaaS-based products.
Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.