Staff Software Engineer

Palo Alto Networks; Santa Clara (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

Palo Alto Networks in Santa Clara, CA is seeking engineers to join our R&D team, tackling projects across Strata, Prisma, and Cortex. You will collaborate across functions to design, develop, and deploy software with agility, using AI-assisted development tools to boost productivity and code quality.

This role emphasizes modern engineering practices, DevOps automation, and continuous learning of AI frameworks to improve developer workflows and product quality.

Qualifications

• BS/MS/PhD degree in Computer Science, Software Engineering, Machine Learning, Cybersecurity, or a similar technical field, with 3-5+ years of professional/equivalent software engineering experience
• Solid understanding of computer science fundamentals, including distributed systems, data structures, algorithms, and operating systems.
• Solid understanding of software development lifecycles (e.g., agile, DevOps) and version control tools like Git.
• Demonstrated problem-solving skills and a willingness to ask questions and work openly with others.

Responsibilities

• Collaborate with cross-functional teams to design, develop, and deploy software solutions with agility and rapid iteration.
• Use and experiment with AI-assisted development tools (e.g., Cursor, Claude Code, internal agents) to boost productivity and improve code quality.
• Help define and evolve new engineering practices that leverage AI for code generation, testing, documentation, and refactoring.
• Write clean, maintainable code and actively participate in peer reviews and team design discussions to ensure alignment.
• Contribute to the automation of development, deployment, and monitoring processes as part of a DevOps culture.
• Continuously learn and apply new AI technologies, frameworks, and techniques that can enhance developer workflows.
• Participate in team retrospectives and help drive improvements in team velocity and product quality.

Skills

Distributed systems

Data structures

Algorithms

Operating systems

Problem solving

Collaborative teamwork

DevOps culture

Education

BS/MS/PhD in Computer Science, Software Engineering, Machine Learning, Cybersecurity

Tools

Git

Docker

Kubernetes

CI/CD pipelines

Observability platforms

Infrastructure as Code

Job description

You will join a Research and Development (R&D) team that will give you the opportunity to make a global impact. One that protects our way of life in the digital age by preventing successful cyber attacks. This team is looking for engineers who are passionate about technology, have an interest in cybersecurity, and want to make a positive difference. In this role, you will gain hands-on experience working on products ranging from our Strata, Prisma, and Cortex organizations.

Key Responsibilities

• Collaborate with cross-functional teams to design, develop, and deploy software solutions with agility and rapid iteration.
• Use and experiment with AI-assisted development tools (e.g., Cursor, Claude Code, internal agents) to boost productivity and improve code quality.
• Help define and evolve new engineering practices that leverage AI for code generation, testing, documentation, and refactoring.
• Write clean, maintainable code and actively participate in peer reviews and team design discussions to ensure alignment.
• Contribute to the automation of development, deployment, and monitoring processes as part of a DevOps culture.
• Continuously learn and apply new AI technologies, frameworks, and techniques that can enhance developer workflows.
• Participate in team retrospectives and help drive improvements in team velocity and product quality.

Required Qualifications

• BS/MS/PhD degree in Computer Science, Software Engineering, Machine Learning, Cybersecurity, or a similar technical field, with 3-5+ years of professional/equivalent software engineering experience
• Solid understanding of computer science fundamentals, including distributed systems, data structures, algorithms, and operating systems.
• Solid understanding of software development lifecycles (e.g., agile, DevOps) and version control tools like Git.
• Demonstrated problem-solving skills and a willingness to ask questions and work openly with others.

Preferred Qualifications

• Exposure to large language models (LLMs) or AI/ML APIs, even through personal projects.
• Familiarity with cloud environments (e.g., GCP, AWS, Azure) and containerized development (e.g., Docker, Kubernetes).
• Experience with modern developer tools such as CI/CD pipelines, observability platforms, and infrastructure-as-code.
• A keen interest in Cybersecurity and protecting the digital world.