Senior Developer, AI Engineering

EisnerAmper — Bangalore

Job Description A QA Engineer for AI Initiatives is responsible for ensuring the quality, reliability, fairness, and performance of AI/ML-powered products and systems. Unlike traditional QA, this role requires deep understanding of non-deterministic model behavior, data quality, and AI-specific failure modes such as hallucinations, bias, and model drift. Key Responsibilities Design and execute test strategies specifically for AI/ML models, LLM-based applications, and data pipelines Develop automated test frameworks for model validation, regression testing, and performance benchmarking Evaluate model outputs for accuracy, consistency, relevance, hallucination, and bias across diverse inputs Test RAG (Retrieval-Augmented Generation) pipelines, chatbots, recommendation systems, and other AI-driven features Collaborate with data scientists and ML engineers to define acceptance criteria and quality thresholds Build and maintain evaluation datasets, ground truth sets, and adversarial test cases Monitor models in production for drift, degradation, and anomalous behavior Validate data quality, data pipelines, and feature stores that feed AI systems Document defects, edge cases, and failure patterns specific to AI behavior Ensure AI systems meet ethical, fairness, and compliance standards (bias audits, explainability checks) Required Skills & Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or a related field 3–6 years of QA experience, with at least 1–2 years in AI/ML quality assurance Strong proficiency in Python for test automation and data analysis Familiarity with LLM evaluation frameworks (e.g., RAGAS, DeepEval, Promptfoo, LangSmith) Hands-on experience with testing tools: Pytest, Selenium, Postman, or similar Understanding of ML lifecycle — training, validation, deployment, and monitoring Knowledge of data quality tools and pipeline testing (Great Expectations, dbt tests) Nice to Have Experience with prompt engineering and red-teaming LLM

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