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AI-native QA specialization reduces pool, but mid-level QA title and 5+ years attract applicants.
Requires AI/ML product testing, LLM and platform experience, limiting transferability across unrelated industries.
Mandatory 5+ years, AI/ML product QA, multi-language coding, contract testing, and CI/CD make filters strict.
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Own the end-to-end test strategy for EG's AI platform and customer-facing product, covering multiple components including SDK, gateway, agent runtime, and more.
Design, build, and maintain test automation frameworks and contract test suites across various programming languages and cloud environments.
Lead performance, load, integration, E2E, and AI output quality testing; integrate test suites into CI/CD pipelines with automated reporting and quality gates.
5+ years experience in software quality engineering with strong hands-on test automation coding.
Proven QA experience specifically in AI/ML product teams, testing AI/ML workloads or LLM-powered applications; this is mandatory.
Proficiency in at least two of Python, .NET/C#, TypeScript.
Experience with CI/CD pipelines, test automation frameworks, contract testing, and performance/load testing tools; cloud-native testing experience on AWS and Azure.
Experienced QA engineer skilled at embedding quality from design through release-readiness in AI-native, multi-cloud platform and product environments.
Capable of leading test strategy and automation implementation across complex integration layers including SDKs, gateways, agent orchestration, and desktop applications.
Has technical credibility to influence engineering teams and promote test-driven development as a quality-first culture driver.