What you'll do: Design and execute end-to-end integration and validation scenarios across multiple product domains. Validate new features and ensure seamless interoperability between distributed system components. Investigate complex cross-component issues through deep technical analysis and root-cause investigation. Analyze application and system logs to identify issues and drive resolution. Develop a strong understanding of system architecture, data flows, and interactions between services. Collaborate closely with Software Engineers, Architects, Product Managers, and cross-functional engineering teams. Participate in feature planning by providing an integration and validation perspective early in the development lifecycle. Continuously improve validation methodologies, engineering processes, and overall product quality. Leverage AI tools to accelerate troubleshooting, technical research, documentation, and engineering productivity. Challenge existing approaches and introduce innovative ideas that improve engineering efficiency and product quality What you should have: 4+ years of experience in System Integration, System Validation, or Software Quality Engineering. Strong experience working with complex distributed software systems. Experience integrating AI tools into engineering workflows. Experience working in Agile development environments. Strong understanding of Linux operating systems. Solid networking knowledge, including TCP/IP, DNS, HTTP/HTTPS, routing, and switching. Experience working with REST APIs, JSON, and YAML. Experience analyzing application and system logs. Excellent troubleshooting and root-cause analysis skills. Strong analytical thinking with the ability to understand complex system architectures. Self-driven, accountable, and comfortable working independently. Curiosity to understand how systems work, not just whether they work. . Nice to have: Experience with Python or another scripting language. Experience with test automation frameworks such as Robot Framework or PyTest. Docker and Kubernetes experience. Experience with telecom technologies (4G, 5G, Open RAN). Familiarity with cloud-native architectures and microservices. Experience using observability platforms such as Grafana, Prometheus, Kibana, or Elasticsearch. Education: B.Sc. in Computer Science, Software Engineering, Electrical Engineering, Computer Engineering, or a related technical discipline.
