Job Overview

Cisco is hiring a Solution Test Engineer in Bangalore for a senior Quality Engineering role focused on end-to-end testing, automation, networking, cloud environments, and modern AI-assisted testing practices. The position involves validating integrated solutions across Cisco hardware, AWS cloud services, web portals, and enterprise networking workflows.

This role is designed for an experienced test engineer who can combine strong programming ability with software testing expertise and practical networking knowledge. The engineer will be expected to build maintainable automation frameworks, validate UI and API behavior, investigate complex defects, and contribute to reliable software delivery through CI/CD quality controls.

The role also has a strong focus on emerging AI capabilities. The successful candidate will use LLM-assisted development tools, agentic approaches, and no-code AI techniques where applicable to improve test coverage, maintain automation assets, and accelerate regression activities.

Key Responsibilities

• Design and develop scalable end-to-end automation frameworks covering UI, API, and integration testing.
• Create test strategies, scenarios, and automation coverage for complex integrated solutions.
• Validate workflows involving Cisco hardware, AWS services, web applications, and enterprise network environments.
• Perform detailed defect investigation, triage, troubleshooting, and resolution support across integrated systems.
• Apply AI-assisted approaches to test automation, including LLM-based development tools and agentic or no-code methods.
• Use AI capabilities to support automated test script generation, test artifact maintenance, and regression execution.
• Model enterprise network environments to validate Layer 2 and Layer 3 protocol behavior and network data flows.
• Test controller and controller-less networking scenarios and integrated network workflows.
• Support CI/CD quality gate integration and help improve automated software delivery practices.
• Contribute to defect governance and quality engineering processes.
• Provide technical guidance and mentoring to mid-level software test engineers.
• Create clear technical documentation and support effective communication across engineering and product teams.

Required Skills

Strong knowledge of software testing principles, quality engineering practices, and different testing methodologies is essential. Candidates should be comfortable designing automation solutions rather than only executing predefined test cases.

Advanced programming ability in Python or Java is required for building custom test frameworks, developing reusable modules, and supporting backend validation. Practical experience with UI automation technologies such as Selenium, Playwright, or Cypress is important.

The role also requires API automation experience using technologies such as REST Assured or PyTest. Candidates should understand how to create reliable API tests and integrate those tests into broader end-to-end validation strategies.

Strong enterprise networking knowledge is another major requirement. Candidates should understand routing and switching concepts at approximately CCNA or CCNP level and be comfortable analyzing network behavior using packet analysis tools such as Wireshark.

The position also requires experience with Linux or Unix environments, AWS cloud services, Docker, Kubernetes, and Splunk log analysis. These skills are important for troubleshooting and validating distributed cloud and on-premises solutions.

Preferred Skills

Experience applying AI to software testing is highly relevant. Candidates who have worked with LLM developer tools, agentic testing approaches, or no-code AI methods can demonstrate additional alignment with the role.

Experience building automation frameworks from the ground up, working with complex enterprise networks, and testing integrated cloud and hardware environments is valuable. Candidates who have contributed to CI/CD quality gates, defect governance, or technical mentoring can also bring relevant experience.

Education

The provided job description does not state a specific degree or formal educational requirement. Candidates should therefore focus their application on demonstrating relevant Quality Engineering experience, programming skills, automation expertise, networking knowledge, and cloud experience.

Experience

The position is listed for professionals with 7 to 10 years of experience, with the mandatory qualifications specifying 7+ years in Quality Engineering. Candidates should have substantial hands-on experience with automated testing, software development, networking, Linux or Unix environments, AWS, containers, and production-oriented troubleshooting.

This is an experienced-level opportunity and is not intended as a fresher or entry-level role.

Required Technologies

The primary technical stack includes Python, Java, Selenium, Playwright, Cypress, REST Assured, PyTest, AWS, Docker, Kubernetes, Linux, Unix, Wireshark, and Splunk.

Additional technical areas include API automation, UI automation, end-to-end testing, integration testing, CI/CD, LLM developer tools, agentic AI, no-code AI approaches, enterprise networking, routing, switching, Layer 2 and Layer 3 protocols, network controllers, and cloud-on-premises integration.

Soft Skills

The engineer should be comfortable solving complex technical problems, investigating defects systematically, and communicating findings clearly. Collaboration is important because the role works across software, networking, cloud, and product environments.

Mentoring ability is also relevant because the position includes technical guidance for mid-level test engineers. A structured approach to test planning, attention to detail, ownership of quality, and willingness to adopt new technologies will help candidates succeed.

Benefits of Working in this Role

This role offers practical exposure to large-scale Quality Engineering across software, networking, cloud, hardware, and AI-assisted automation. Engineers can work with technologies including Python, Java, Kubernetes, AWS, modern UI automation frameworks, API testing tools, and observability platforms.

The position also provides an opportunity to work on advanced testing challenges involving enterprise network topologies and emerging AI approaches. The combination of automation, cloud, networking, and AI skills can support long-term growth in senior Quality Engineering and test architecture careers.

Work Mode

The job is listed as Hybrid. Candidates should be prepared to follow the applicable hybrid working arrangement for the Bangalore team.

Location

The position is based in Bangalore, India, within Cisco's Product and Engineering organization.

Who Should Apply

This opportunity is suitable for experienced Solution Test Engineers, Senior QA Automation Engineers, Quality Engineers, Test Automation Engineers, and Software Test Engineers with 7 to 10 years of relevant experience.

Strong candidates should be able to demonstrate hands-on programming in Python or Java, UI and API automation experience, enterprise networking knowledge, and practical experience with AWS, Linux or Unix, Docker, Kubernetes, and Splunk. Professionals with experience using AI-assisted testing techniques are particularly relevant.

Career Growth

Experience in this role can support progression toward Senior Quality Engineer, Lead Test Engineer, Automation Architect, Solution Test Architect, Quality Engineering Manager, or specialized engineering roles spanning cloud, networking, and AI-driven testing. Building expertise across automation and infrastructure can also broaden opportunities in modern software delivery organizations.

Application Advice

When applying, highlight measurable examples of automation framework development, end-to-end testing, API validation, UI automation, and complex defect troubleshooting. Clearly mention your experience with Python or Java and tools such as Selenium, Playwright, Cypress, REST Assured, and PyTest.

Also emphasize enterprise networking knowledge, Wireshark usage, AWS experience, Docker, Kubernetes, Linux or Unix, and Splunk. If you have applied LLMs, agentic AI, or no-code AI tools to testing, explain how they improved coverage, maintenance, or regression efficiency. Include examples of mentoring and CI/CD quality integration where applicable.