Ecological differences among species influence population response to historical environmental changes, and genetic simulations now allow us to directly incorporate this variation into inferential models. However, the impact of life history strategies in demographic inference has been far less explored relative to the impact of other ecological differences, such as dispersal capacity and habitat preference. Here, we utilize individual-based simulations of a non-Wright-Fisher population to ask whether differences in the average age of first reproduction of individuals, the average adult mortality and the average number of mates per reproductive season lead to consistent and predictable differences in summary statistics of genetic diversity commonly used for simulation-based parameter estimation and demographic inference. Using a Random Forest model, we estimate three population parameters (variance in reproductive success, generation time, and effective population size) from genome-wide SNP variation for two bird species with distinct life history strategies that are directly built into the simulation machinery. Our results show that life history variation leads to predictable differences in patterns of genetic diversity. While prediction accuracy is low, parameter estimates from empirical datasets agree with the expectation that species with extreme polygamy, long adult longevity and later onset of reproduction will exhibit higher variance in reproductive success, longer generation time and smaller effective population sizes. Since the signal of life history differences is observed in the genetic summary statistics, we suggest that simulation- and model-based multi-species demographic inference should incorporate life history parameters.