Kobiela et al. develop a risk-averse optimization framework for genetic circuit design that combines Bayesian inference, Thompson sampling, and risk management. The method can leverage data from previous designs, including failures, to recommend new robust designs. Results include application to adaptation circuits and genetic oscillators.