Palo Alto Networks is looking to solve complex problems in the engineering productivity and platform space to empower thousands of engineers to develop and deliver their products with the highest quality and velocity while ensuring security throughout the lifecycle. This involves improving source code management, build and test tooling, and end-to-end CI/CD pipeline workflows.
Requirements
- Proficiency in object-oriented programming languages such as Python, Javascript, Go (Nice to have)
- Experience with web frameworks such as Django, NodeJS, React
- Knowledge of containerization technologies (Docker, Kubernetes)
- Proficiency in algorithms, data structures, Relational DB (Postgres), and system design
- Understanding of Unix/Linux, SSH, and networking fundamentals
- Experience with cloud platforms (GCP, AWS and Azure)
- Knowledge of infrastructure as code (IaC) and config mgmt tools like Terraform and ansible
Responsibilities
- Implement the infrastructure, tools and frameworks needed to keep our thousands of developers in sync while sharing code, building, testing, releasing, and deploying their applications and services continuously
- Design, build and maintain tools and frameworks to automate the commit-deploy pipeline (including development, testing, release/deployment and monitoring) of our products and services
- Design, develop, and maintain comprehensive CI/CD templates for use across various engineering teams
- Simplify and increase visibility into the CI pipelines and enable easier and faster insights into potential problems
- Monitor the performance and health of the engineering productivity tools
- Troubleshoot and resolve issues promptly to minimize downtime and impact on developer productivity
- Identify opportunities for automating repetitive tasks, improving workflows, and enhancing overall developer productivity
Other
- Set the example for high levels of accountability
- Execute and deliver impact both individually and through the team
- A working knowledge of foundational AI/ML concepts and experience leveraging relevant AI tools, libraries, or APIs to enhance engineering workflows
- A proven ability or keen interest in applying Generative AI and other intelligent technologies to optimize developer processes
- An ability to understand and utilize relevant engineering data to identify opportunities for AI/ML integration that drives measurable improvements in developer efficiency and output quality
