This article introduces a pilot-activated recovery system (PARS) for advanced jet trainers that uses an advanced reinforcement learning (RL) architecture, specifically a Soft Actor-Critic (SAC) model, to improve operational efficiency and aircraft upset recovery while considering negative-g forces on the pilot. The system outperforms conventional control methods in expert evaluations.