As the bioprocessing and synthetic biology spaces rapidly expand, post-transcriptional regulation is emerging as driver for maximizing signal response rate and for minimizing cost per protein within cells. Designing robust post-transcriptional control systems that have precise tunability and can achieve diverse regulatory outcomes are paramount to advance the field. Herein, we develop a new approach for engineered post-transcriptional control in bacteria by rewiring a native regulatory system inEscherichia coli, the Carbon Storage Regulatory (Csr) Network, to create tunable, complex genetic circuits. First, by co-opting native components of the Csr Network to regulate translation of a target mRNA transcript, we establish a Csr-regulated Buffer Gate. Next, by rationally engineering the interactions between our synthetic construct and the native components of the Csr Network, we expand our original design into a genetic toolbox of 12 Buffer Gates that achieve precise tunability across a 10-fold range of target gene expression. Subsequently, to further regulatory capabilities using this approach, we develop a Csr-regulated NOT Gate through engineering a Csr-activated sequence into our synthetic constructs. We then build upon the Csr Buffer and Not Gates to create post-transcriptional dual input Boolean OR, NOR, AND and NAND Logic Gates, as well as a genetic pulse circuit. As a third step, we demonstrate portability of our Csr-regulated Buffer Gates into three industrially relevant bacteria by recapitulating Buffer Gate activity simply by leveraging the conserved homologous Csr Network in each species. Lastly, as a demonstration of downstream application, we apply our system to a proof-of-concept synthetic mevalonate pathway. Using our engineered constructs, we optimize mevalonate production inE.coli resulting in a three-fold increase in production relative to a transcriptionally controlled mevalonate pathway. As a whole, we establish a novel approach to rewire post-transcriptional regulatory networks for complex bacterial computation that can be utilized for efficient bioproduction in engineered microbes.