Cisco

Overview

As part of the Quality Engineering organization, you will play a critical role in validating next-generation Catalyst switching platforms and software features. You will collaborate with engineering, product management, architecture, and customer support teams to ensure exceptional product quality through comprehensive testing, automation, and AI-assisted validation methodologies.

About Cisco

At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds.

Requirements & Eligibility

• Bachelor’s or Master’s Degree in Computer Science, Electronics, Information Technology, or a related field.
• 1+ years of experience in Software QA, System Validation, or Network Testing.
• Strong experience testing enterprise switching and networking products.
• Strong automation experience using Python.
• Hands-on experience with REST APIs, NETCONF, RESTCONF, YANG, JSON, and YAML.
• Experience using automation and testing frameworks such as PyTest, Robot Framework, or equivalent.
• Strong Linux fundamentals including scripting, troubleshooting, and system administration.
• Experience with virtualization and container technologies such as VMware, KVM, Docker, or Kubernetes.

Key Responsibilities

• Define and drive test strategies for Catalyst 9000 switching platforms, ensuring comprehensive validation across functional, scale, performance, resiliency, interoperability, and security domains.
• Design, develop, and maintain scalable test automation frameworks using Python and modern automation technologies.
• Lead end-to-end validation of Layer 2, Layer 3, security, management, and platform software features.
• Develop automated test suites for feature validation, regression testing, system integration testing, upgrade testing, and customer deployment scenarios.
• Collaborate closely with software developers, architects, and product managers to understand feature requirements and define robust validation plans.
• Leverage AI-assisted development tools such as GitHub Copilot, Codex, Claude, and VS Code extensions to improve automation productivity, test coverage, and engineering efficiency.
• Build and enhance CI/CD-based validation pipelines to enable continuous testing and faster release cycles.
• Perform root-cause analysis of complex networking and software issues using protocol-level debugging and packet analysis tools.