Principal Software Automation/Test Engineer

Palo Alto Networks

1d•Onsite

About The Position

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.

Requirements

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.

Nice To Haves

Experience in cloud security or an equivalent relevant domain is advantageous.

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.