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.