QA Automation Engineer - Network and Distributed Systems

Role Overview

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.

What You’ll Work On

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

Key Responsibilities

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

Technical Expectations

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

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

What Makes This Role Different

You won't just test whether an API returns the expected response. You'll ask:

"What happens when the network behaves badly?"

Can the system detect it?

Can it recover?

Does it fail safely?

Are the right signals generated?

Can we automatically validate that behavior?

That's the kind of QA engineering we're looking for.

About Ciroos

We are an early-stage AI startup focused on Site Reliability Engineering (SRE) . Rather than being another observability platform, its goal is to act as an AI SRE teammate that works alongside SRE, DevOps, Platform Engineering, Cloud Operations, and IT Operations teams to investigate incidents, determine root causes, and automate remediation.

Our team includes experienced entrepreneurs and engineers who have built multiple billion-dollar products from scratch. As a well-funded US-based company backed by top-tier VCs, we have offices in the US, India, and Europe. Join us in our fast-paced environment where you’ll have a front-row seat to shape the future of AI-driven Observability solutions.