QA Automation Engineer - Network & Systems

We are looking for a QA Automation Engineer with strong networking and distributed-systems expertise who can operate at the intersection of quality, reliability, and system-level testing. This goes far beyond a traditional QA role. In this role, you'll build automation that tests the limits of complex systems under real-world stress, network chaos, and massive scale. You will work closely with infrastructure, Kubernetes, and distributed networks to break things in staging so they never break in production.

Responsibilities:

• Kubernetes-based distributed systems and multi-cluster environments.
• Network-heavy distributed systems and service-to-service communication
• L2/L3 networking and cloud networking scenarios.
• Load balancers, VPCs, routing, DNS, and connectivity.
• Network failures, latency, packet loss, and service degradation.
• Observability and alerting pipelines.
• Reliability validation and failure-injection testing.
• API, integration, system, and end-to-end automation.
• Infrastructure and deployment automation.
• CI/CD pipelines and reliability gates.
• Design and build scalable automation frameworks for network, API, integration, and system-level validation.
• Build automated tests for service-to-service communication and distributed workflows.
• Validate system behavior under network failures, latency, packet loss, connectivity issues, and partial failures.
• Develop failure-injection and reliability tests for distributed systems.
• Validate Kubernetes networking and multi-cluster behavior.
• Integrate automated validation into CI/CD pipelines.
• Analyze failures across logs, metrics, traces, and network signals.
• Partner with SRE, Platform, and Backend teams to make systems more testable and observable.
• Perform deep-dive root cause analysis on system and network failures.
• Build reusable testing utilities and infrastructure.
• Help establish reliability and quality standards across the platform.

Requirements:

• Deep expertise in networking fundamentals and distributed systems, TCP/IP, DNS, HTTP/HTTPS and service communication, Kubernetes networking, network failure modes and troubleshooting, distributed-system failure scenarios, observability, and production debugging.
• Strong hands-on experience with Kubernetes / multi-cluster environments, AWS, Azure, or GCP networking, VPCs, load balancers, routing and IAM, network troubleshooting and debugging, API and integration testing, chaos / failure-injection testing, and CI/CD automation.

Programming:

• Strong coding skills in Python and Go (mandatory).
• Experience building automation frameworks and system-level tooling.
• Proficiency in Shell scripting and infrastructure automation.