QA Automation Engineer - Network and Distributed Systems
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Before you apply
LocationBengaluru
Work modeon-site
Typefull-time
SenioritySenior
DepartmentEngineering
Company size51–200 people
PostedAug 31, 2026 · 2mo ago
Verified live4h ago
At a glanceSummarised by Seekless from the posting.
QA Automation Engineer with strong networking and distributed-systems expertise
Strong coding skills in Python and Go (mandatory)
Experience building automation frameworks and system-level tooling
Proficiency in Shell scripting and infrastructure automation
Deep expertise in networking fundamentals and distributed systems
Deep expertise in TCP/IP, DNS, HTTP/HTTPS and service communication
Deep expertise in Kubernetes networking
Deep expertise in network failure modes and troubleshooting
Deep expertise in distributed-system failure scenarios
Deep expertise in observability and production debugging
Strong hands-on experience with Kubernetes / multi-cluster environments
Strong hands-on experience with AWS, Azure or GCP networking
Strong hands-on experience with VPCs, load balancers, routing and IAM
Strong hands-on experience with network troubleshooting and debugging
Strong hands-on experience with API and integration testing
Strong hands-on experience with chaos / failure-injection testing
Strong hands-on experience with CI/CD automation
Skills
Kubernetes
Python
Go
AWS
Azure
GCP
TCP/IP
DNS
HTTP
HTTPS
Jenkins
Shell scripting
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
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Kubernetes-based distributed systems and multi-cluster environments
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Network-heavy distributed systems and service-to-service communication
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L2/L3 networking and cloud networking scenarios
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Load balancers, VPCs, routing, DNS and connectivity
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Network failures, latency, packet loss and service degradation
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Observability and alerting pipelines
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Reliability validation and failure-injection testing
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API, integration, system and end-to-end automation
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Infrastructure and deployment automation
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CI/CD pipelines and reliability gates
Key Responsibilities
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Design and build scalable automation frameworks for network, API, integration and system-level validation
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Build automated tests for service-to-service communication and distributed workflows
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Validate system behavior under network failures, latency, packet loss, connectivity issues and partial failures
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Develop failure-injection and reliability tests for distributed systems
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Validate Kubernetes networking and multi-cluster behavior
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Integrate automated validation into CI/CD pipelines
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Analyze failures across logs, metrics, traces and network signals
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Partner with SRE, Platform and Backend teams to make systems more testable and observable
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Perform deep-dive root cause analysis on system and network failures
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Build reusable testing utilities and infrastructure
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Help establish reliability and quality standards across the platform
Technical Expectations
Deep Expertise In
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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
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You won’t just test whether an API returns the expected response. You’ll ask:
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“What happens when the network behaves badly?”
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Can the system detect it?
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Can it recover?
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Does it fail safely?
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Are the right signals generated?
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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.