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Niche AI-assurance skills reduce applicant density, but mid-level and metro location increase competition.
Highly domain-specific AI assurance and regulatory testing make the role industry-specialized and less transferable.
Explicit 5–7 years requirement, mandatory AssureAI, Python, CI/CD, and regulatory expertise.
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Build and maintain evaluation datasets and scenarios for AssureAI's 19 Trustworthiness checks across Gemini-based AI agents.
Run bias, toxicity, red-team, and explainability test suites on commit; triage failures and manage CI/CD threshold gates to block releases on failures.
Package audit evidence and track dataset coverage gaps as agent domains expand, collaborating to scale evaluation throughput with another AssureAI Engineer.
5-7 years in QA/test engineering for ML or GenAI systems, ideally with a dedicated evaluation framework (DeepEval, Ragas, Promptfoo, or comparable).
Hands-on experience with AssureAI or a directly comparable AI-assurance/evaluation platform.
Proficient in Python and comfortable integrating test suites into CI/CD pipelines (Cloud Build, GitHub Actions).
Working knowledge of AI regulatory requirements (EU AI Act, NIST AI RMF, ISO/IEC 42001) sufficient to translate regulations into test coverage.
Experienced operator accustomed to managing multiple failing checks across various AI agents and coordinating with multiple technical roles for issue resolution.
Strong domain expertise in AI trustworthiness evaluations including bias/fairness testing, explainability techniques (SHAP/LIME), and adversarial red-teaming.
Familiar with regulatory compliance testing and audit evidence packaging workflows to support governance review processes.