Six specialized AI agents coordinate via a cloud-native microservices infrastructure to automate software quality assurance. The AINTMA architecture uses reinforcement learning for prioritization and LLMs for quality intelligence. This framework replaces manual test management with autonomous decision-making. Practitioners can now automate risk assessment and execution orchestration within distributed cloud environments.