Automation Network Engineer

As a Test Automation Engineer, you will bridge the gap between hardware and software integration by developing automated test solutions for our industry-leading Wavence Microwave transmission systems. Working in a vibrant, global environment, you will leverage modern CI/CD pipelines and emerging AI methodologies to drive growth in testing efficiency and reduce negative manual bottlenecks. We foster a culture of fearless innovation, and we are looking for resilient engineers who embrace trial and error to conquer complex challenges. Automated Test Development: design, write, and execute automated test scripts to validate Wavence microwave hardware and software against internal specifications and global standards. Hardware & Software Integration: integrate and verify components for microwave links, packet microwave routers, and digital transmission equipment in a lab environment. Lab Management: set up, calibrate, and maintain RF/microwave laboratory equipment (e.g., spectrum analyzers, signal generators) alongside associated automation tools. Process & Pipeline Improvement: drive continuous delivery by integrating automated tests into modern CI/CD pipelines, challenging the status quo of daily operations. AI Integration: Explore and implement AI/ML tools to optimize test case generation, automate log analysis, and improve predictive debugging. Global Collaboration & Leadership: work cross-functionally with R&D, hardware, and software teams worldwide, providing technical leadership and training on automation best practices and microwave safety. Experience: hands-on experience (or relevant Master’s/PhD research) focused on Microwave Transmission, Telecom, Networking, or Systems and Signals. Core Technologies: knowledge of Telecom / Microwave technologies (point-to-point/multipoint), Digital Transmission (TDM/IP), and IP Networking (Traffic & Routing). Test Automation & Scripting: programming experience (Python, XML, YAML, Shell) with a proven track record using modern test automation tools (Robot Framework and/or Selenium highly preferred). CI/CD & Infrastructure: some experience building and maintaining CI/CD pipelines (Git/Gerrit, Jenkins, Jira) across Windows and Linux environments. AI/ML Familiarity: good understanding of AI/ML libraries, generative AI tools, or data analytics techniques to modernize test automation. Mindset: self-motivated and adaptable, thrive in multicultural teams, think outside the box, and are unafraid to pivot or experiment when initial solutions fail.