SW Testing Principal Engineer

Amdocs•Alpharetta, GA

18h•Onsite

About The Position

Amdocs helps the world’s leading communications and media companies deliver exceptional customer experiences through reliable, efficient, and secure operations at scale. We provide software products and services that embed intelligence into how work runs across business, IT, and network domains –delivering measurable outcomes in customer experience, network performance, cloud modernization, and revenue growth. With our talented people, and more than forty years of experience running mission-critical systems around the globe, Amdocs runs billions of transactions daily. Our technology is relied on every day, connecting people worldwide and advancing a more inclusive, connected world. Together, we help those who shape the future to make it amazing. Amdocs is listed on the NASDAQ Global Select Market (NASDAQ: DOX) and reported revenue of $4.53 billion in fiscal 2025. For more information, visit www.amdocs.com. At Amdocs, our mission is to empower our employees to 'Live Amazing, Do Amazing' every day. We believe in creating a workplace where you not only excel professionally but also thrive personally. Through our culture of making a real impact, fostering growth, embracing flexibility, and building connections, we enable them to live meaningful lives while making a difference in the world. We are seeking a SW Testing Principal Engineer with 12+ years of experience to serve as the technical authority and strategic leader for our automation team. In this high-impact role, you will oversee the quality of complex Telecom OSS and Network systems, integrating Cloud-native architectures and AI-driven automation. You will balance deep hands-on expertise in Python and Robot Framework with the leadership required to manage teams through intricate software deliveries and drive the future of our testing ecosystem.

Requirements

Education: Bachelor’s degree in computer science, Engineering, or a related field.
Experience: 12+ years in Software Engineering/QA, with 3–5 years specifically managing teams through complex software deliveries. (Minimum 5+ years of total leadership experience).
Technical Mastery: Proficiency in test automation frameworks (Python/Robot Framework) and an expert understanding of testing methodologies, tools, and best practices.
Cloud & AI: Practical exposure to Cloud platforms (AWS/Azure/GCP) and an understanding of how AI/ML can enhance the Software Testing Life Cycle (STLC).
Modern Processes: Deep understanding of Agile, Scrum, and DevOps processes, including CI/CD orchestration and defect tracking tools (e.g., Jira).
Domain Expertise: Deep knowledge of Telecom OSS and Network call-flows.
Communication: Excellent leadership skills for team management and stakeholder collaboration, with the ability to translate complex quality metrics into actionable insights.

Responsibilities

Develop and implement comprehensive test strategies and plans tailored for complex, multi-layered Telecom software deliveries.
Manage and mentor a team of test engineers and QA professionals. Foster a high-performance culture rooted in a "Growth Mindset," technical curiosity, and professional empathy.
Coordinate and oversee all testing activities, including System, Integration, and User Acceptance Testing (UAT), ensuring seamless data flow across integrated systems.
Lead all test automation efforts, championing the use of Python and Robot Framework while promoting the adoption of AI-based testing tools.
Partner with project managers and development teams to align testing efforts with project timelines and high-level business objectives.
Monitor and report on testing progress, quality metrics, and defect tracking. Ensure all activities comply with established quality standards and industry best practices.
Proactively identify and mitigate risks related to testing processes and project deadlines, ensuring reliability in high-pressure delivery cycles.
Modernize the testing ecosystem by integrating Cloud-native architectures and AI-driven capabilities (e.g., predictive analytics, intelligent defect detection).