Most ML researchers and leading-edge folks want Python, and there's always a lot of demand for making things faster/easier/etc. Adding more first-class languages is on the "should do" list, but it adds a long-lived support burden to keep the language bindings in sync with the core. There are some fairly deep questions about how to make it easy to have good, first-class language support across many languages without multiplying the work by a factor of N. For example, Andrew Myers is spending some time on the team and has been working on beefing up the Java support, but as you can probably infer from this PR, it's ... complicated. The discussion in this PR is a pretty good glimpse into some of the underlying issues surrounding first-class language support.
https://github.com/tensorflow/tensorflow/pull/11251
So - your concern is absolutely founded, and is taken very seriously, but is treated cautiously for bigger-picture reasons. I'd expect continued progress on this front, but I wouldn't expect it on very short time horizons.