Senior AI-Driven Integration & Validation Engineer

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.