Python Automation lead Wi-Fi or Telecom

We are looking for an Automation QA Software Engineer to join our team supporting automated testing for Charter’s CPE/Wi-Fi product lines. This role focuses on validating firmware releases, Wi-Fi features, cloud integrations, and stability scenarios across multiple OEM router platforms. You will work closely with firmware developers, WIST, SCPS, CUJO, and DevOps teams to ensure high-quality releases and reliable automation pipelines.

Key Responsibilities
• Design, develop, and maintain automated test cases using Python + Robot Framework for end-to-end development of Wi-Fi routers and client devices.
• Work with DAL (Data Access Layer), SCL, SCPS, and cloud APIs to retrieve configuration and telemetry.
• Automate key areas such as firmware upgrade/downgrade, reboot cycles, SSH/CLI scenarios, WAN/LAN connectivity, Wi-Fi performance, MAP-T, security features, and device stability.
• Execute automated suites in GitLab CI/CD pipelines and work with DevOps on integration and failure triage.
• Analyze test results, identify defects, categorize failures (code/lab/hardware/existing bug), and work with partners to drive closure.
• Contribute to automation improvements including reliability, flakiness reduction, resource optimization, and pipeline speed.
• Support multiple OEM models across Spectrum labs with 80+ chambers and remote lab access.
• Collaborate with onsite/offshore teams to meet delivery milestones and maintain test coverage targets.
• Document test plans, automation design, test execution results, and best practices.

Required Skills
• Strong experience in Python and automation frameworks (Robot Framework preferred).
• Hands-on knowledge of networking fundamentals: DHCP, DNS, TCP/IP, Wi-Fi standards (Wi-Fi 6, 6E, 7), IPv6, MAP-T, routing.
• Experience working with Linux/Unix, SSH/CLI, and embedded devices.
• Familiarity with GitLab pipelines, Git, and CI/CD workflows.
• Ability to analyze logs, debug failures, and isolate reproducible defects.
• Good communication skills and ability to work with both onsite and offshore teams.

Experience with AI/ML for test automation (log analysis, anomaly detection, predictive testing)