For any distribution $π$ with support equal to $[n] = \{1, 2,..., n \}$, we study the set $\mathcal{A}_π$ of tridiagonal stochastic matrices $K$ satisfying $π(i) K[i,j] = π(j) K[j,i]$ for all $i, j \in [n]$. These matrices correspond to birth and death chains with stationary distribution $π$. We study matrices $K$ drawn uniformly from $\mathcal{A}_π$, following the work of Diaconis and Wood on the case $π(i) = \frac{1}{n}$. We analyze a `block sampler' version of their algorithm for drawing from $\mathcal{A}_π$ at random, and use results from this analysis to draw conclusions about typical matrices. The main result is a soft argument comparing cutoff for sequences of random birth and death chains to cutoff for a special family of birth and death chains with the same stationary distributions.