Safe AI deployment is the set of engineering and governance practices applied when releasing an AI system into production so that it operates within intended bounds, degrades gracefully, and remains subject to human oversight. It draws on techniques from AI safety and AI alignment, including staged rollouts, monitoring, kill switches, and red-teaming, to reduce the risk of harmful or unintended behaviour once a model is exposed to real users. It is the operational counterpart to alignment research, translating safety properties validated offline into guarantees that hold in live systems.