QA Automation Engineer - Cloud & Infrastructure

Cloud infrastructure and distributed systems

Kubernetes architecture and troubleshooting

Cloud failure modes and reliability

Multi-cluster environments

Observability and production debugging

Infrastructure automation

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

Strong coding skills in Python and Go (mandatory)

Experience building automation frameworks and system-level tooling

Proficiency in Shell scripting and infrastructure automation

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?

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.

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.