Employer description & source details
We are looking for an AI-Native Software Engineer focused on QA Automation . This is not a role for someone who simply clicks through test cases. This is a software engineering role for someone who builds systems that prove whether the product works. Our developers build with AI agents. That means code can arrive faster than traditional QA can review it by hand. We need a QA automation engineer who can build the testing harness, automated checks, synthetic data, test environments, and agent-driven QA workflows that keep up with agent-speed development . Here is the test: can you build a test system, seed a real bug, prove the test catches it, and explain what is still unverified? We are not looking for someone who signs off work because it “looks fine.” We are looking for someone who demands evidence. QA at Zenara is not a downstream gate. It is an engineering platform. We are building toward a system where product requirements can become test plans, test data, automated browser and API checks, evidence reports, failure routing, and release confidence — with agents helping create and run the work, and engineers governing the quality. You will help design and operate this QA system, including: Quality metrics and release confidence The goal is not to automate bad testing. The goal is to build a system that catches real defects before customers do. Build and maintain the QA automation harness across browser, API, data, and workflow layers. Create automated checks that run on every meaningful change. Build synthetic test data and isolated test environments. Own the UAT/QA automation pipeline from requirement to test plan to run to evidence. Use AI agents to help generate, execute, improve, and debug tests. Build independent agent-driven QA workflows that test the work of c
Extracted skills: typescript, react, node.js, postgresql, redis, azure, terraform