QA Automation Engineer - Cloud & Infrastructure

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.