Copy of AI QA Test Engineer
2 weeks ago
About the Role
Experienced AI QA Test Engineer to ensure the quality, reliability, and ethical performance of AI-driven systems and applications. This role requires a deep understanding of AI/ML workflows, data validation, model testing techniques, and automation frameworks. The ideal candidate is highly analytical, detail-oriented, and passionate about building trusted AI products.
Participates in QA activities on project assignments and ensures timely delivery on QA commitments in a fast-paced product development environment.
Review of functional requirements and technical design documentation and creation of test plans, test scenarios and test cases. Execution of test plans and certification of application releases
Key Responsibilities:
AI/ML Testing
Validate ML models, data pipelines, and inference APIs for accuracy, fairness, and robustnessEvaluate model behavior across diverse data sets, edge cases, and unexpected inputsMonitor model drift, performance degradation, and bias over timeConduct prompt testing, hallucination detection, and safety validation for LLM-based systemsExperience of testing implementation of AI/ML into applicationManual Testing with automation exposureAPI testing with SOAP UI/ PostmanAgile methodology experienceTest & Defect management with JIRA/ Azure DevOps (ADO)DB Testing Experience - Good to Have Tools - Deepeval/ Langfuse/ PytestQuality Engineering & Automation
Build and maintain automated test suites for AI featuresDevelop test scripts for ML workflows using Python, Playwright, and CI/CD toolsDesign and execute manual and automated tests for functional, performance, and security scenariosIdentify defects, establish test metrics, reporting dashboards, and test traceabilityData Quality & Responsible AI
Validate training and inference data quality, labeling consistency, and data governanceWork with data science and product teams to implement responsible AI testing guidelinesDocument and escalate risks related to bias, privacy, explainability, and complianceCross-Functional Collaboration
Partner with Data Scientists, ML Engineers, and Product Managers to define acceptance criteriaParticipate in design reviews, model evaluations, and release readiness checkpointsContribute to QA strategy and Test PlansRequired Qualifications
Bachelor's degree in computer science, Engineering, or related field (or equivalent experience)4+ years of experience in software QA engineering2+ years working with AI/ML or data-centric systemsStrong Python programming skillsProficiency in automation frameworks (e.g., Playwright, WebdriverIO, Selenium)Experience with ML platforms (TensorFlow, PyTorch, Hugging Face, MLflow, etc.)Hands-on experience testing APIs, data pipelines, and distributed systemsExposure to RAG pipelines and agent frameworksFamiliarity with prompt testing and LLM evaluation techniquesExperience with model evaluation metrics (precision, recall, F1, ROC-AUC, BLEU, perplexity, etc.)Knowledge of MLOps, CI/CD, and cloud platforms (AWS, Azure, or GCP)Familiarity with Responsible AI frameworks (NIST AI RMF, ISO/IEC standards, fairness toolkits)Experience testing vector databases and AI search (Pinecone, Elasticsearch, Redis Vector)Key Skills
AI/ML testing & analysisAutomation & scriptingData validation & pipelinesRisk, ethics, & compliance mindsetStrong problem-solving & debugging skillsExcellent documentation & communication skillsWorking with distributed teams-
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