Role Overview
We are looking for a QA Automation Engineer with strong cloud and infrastructure expertise who can operate at the intersection of quality, reliability, and system-level testing.
You will build automation that validates complex cloud-native systems across Kubernetes and multi-cloud environments. You'll test not just whether a feature works, but whether the underlying infrastructure remains reliable under scale, failure, and operational stress.
What You’ll Work On
Kubernetes-based distributed systems
AWS, Azure and GCP environments
Multi-cloud and multi-cluster infrastructure
Infrastructure and deployment automation
Kubernetes workload and cluster validation
Cloud service integrations
Observability and alerting pipelines
Reliability validation and chaos testing
API, integration and end-to-end automation
CI/CD reliability gates
Key Responsibilities
Design and build scalable automation frameworks for cloud infrastructure and system-level validation
Automate validation of Kubernetes clusters, workloads and deployments
Test cloud infrastructure across AWS, Azure and GCP
Validate infrastructure changes and deployment workflows
Build automated tests for multi-cluster and distributed environments
Design failure-injection and chaos scenarios for cloud infrastructure
Validate system behavior during infrastructure and service failures
Integrate automated validation into CI/CD pipelines
Analyze failures using logs, metrics and traces
Partner with SRE, Platform and Backend teams to improve system reliability and testability
Lead root cause analysis of infrastructure and production failures
Build reusable automation utilities and validation tooling
Establish reliability gates that prevent defective infrastructure or deployments from reaching production
Technical Expectations
Deep Expertise In
Cloud infrastructure and distributed systems
Kubernetes architecture and troubleshooting
Cloud failure modes and reliability
Multi-cluster environments
Observability and production debugging
Infrastructure automation
Strong Hands-on Experience With
AWS / Azure / GCP
EKS, GKE or managed Kubernetes platforms
Docker and Kubernetes
Infrastructure-as-Code
CI/CD pipelines
Cloud networking fundamentals
Chaos testing and reliability engineering
API and system-level testing
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 be testing how a distributed cloud-native system behaves under real-world conditions — at scale, across clusters, and when things fail.
You'll build automation to answer questions like:
What happens when infrastructure fails?
Can the system detect it?
Does it recover correctly?
Can we validate that behavior automatically before it reaches production?
The goal isn't just to find bugs. It's to build systems that can prove they are reliable.
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.
