This case study reports on the perceptions and dialogic behaviors of 15 preservice K-12 teachers engaging in simulation-based teaching practice with AI-powered student agents. Data included transcripts of text-based classroom dialogue, interviews, observations, and conversation logs. Using mixed-methods analyses and a framework of ambitious science teaching, we identified two key findings that are important to Human-AI interaction researchers and teacher trainers. First, AI-powered student agents exhibit naturalistic discourse behavior, with ambitious talk moves leading to more rigorous student contributions and conservative talk moves leading to low rigor contributions. And second, preservice teachers' dialogue was responsive to the AI-powered students' contributions.