AI QA Engineer

Required Skills & Experience

-5+ years of QA, quality engineering, or software testing experience in data or AI-heavy environments

-Hands-on experience testing AI systems, including RAG pipelines, LLM-based applications, and vector search systems

-Python skills for test automation, data validation, and framework development

-Experience testing cloud data pipelines and workflows in Snowflake and at least one major cloud (AWS or Azure)

-Experience with OCR/document extraction validation (e.g., Azure Document Intelligence, AWS Textract)

-Strong understanding of the end-to-end AI lifecycle and common failure modes of LLM systems

-Experience building automated tests for APIs, data transformations, and distributed systems

-Solid understanding of software engineering best practices: CI/CD integration, test design, debugging, and evaluation

-Strong communication and collaboration skills, with an ability to partner with cross-functional teams

Job Description

Insight Global is seeking an AI QA Engineer to join one of our medical device clients local to India. In this role, you will work across Snowflake, AWS, and Azure while partnering closely with AI Data Engineers, AI Engineers, and Product teams to develop robust testing frameworks for RAG pipelines, vector stores, OCR workflows, LLM applications, and AI‑enabled services. You will design and implement comprehensive QA strategies covering every stage of the AI lifecycle—from data ingestion and preprocessing to embedding creation, vector indexing, retrieval accuracy, model inference, and deployment. This role involves building automated test suites for APIs, data pipelines, and retrieval systems; validating the correctness and performance of vector databases and embedding workflows; and ensuring document‑processing systems powered by Azure Document Intelligence, AWS Textract, and similar tools are functioning reliably. You will help integrate automated testing into CI/CD workflows, contribute to the creation of evaluation metrics and monitoring dashboards, and champion QA best practices to elevate our organization’s overall quality maturity. Ultimately, you will play a critical role in ensuring that our AI systems consistently deliver accurate, compliant, and trustworthy outcomes.