The rise of large-scale AI systems built on distributed architectures presents unique challenges for ensuring responsible AI practices. Traditional distributed systems issues intersect with ethical considerations, complicating the development of transparent, fair, and reliable AI. Drawing on real-world production examples, this presentation highlights these challenges and proposes actionable solutions that prioritize ethical AI deployment without compromising system performance or scalability.