I'm looking for a way to visualize chip-seq peaks from multiple data sets integrated onto one gene of interest. I do not necessarily need to look at the pile-ups of reads (like on the genome browser) but a way to mark locations of certain peaks on a gene from multiple data sets. I'm stuck on how to accomplish this.
If a UCSC Genome Browser view wouldn't work for you, perhaps you could repurpose a lollipop plot to show peak maxima over gene annotations.
IGV or UCSC genome browser are most likely your best bet
If you are looking for an exploratory analysis directly from the command line you could try ASCIIGenome (I'm the author). Something like:
ASCIIGenome gene.bed chipseq1.bed chipseq2.bed ...
Would give you something like this 
With karyoploteR you plot the peaks from the different timepoints in a single "track" creting an overlay. Depending on the format of your data you could either peak intervals with kpPlotRegions or kpRect or plot the exact peak shape with kpLines. You can find more examples at karyoploteR tutorial and examples page
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version 2.3.6
I like the visualization on UCSC but then I'm stuck with a stack of tracks with each set of peaks represented on the gene in each track (unless there is a better way that I'm unaware of). What I'm after is one overall view of the gene and then an overlay of the peak positions from the different data sets - it's a time course.
Take a look at modifying a lollipop plot. You could take a gene annotation (one for a gene-of-interest) and add markers (i.e., "lollipops") where there are time-course ChIP-seq peak maxima, or time-course points at which a ChIP-seq peak interval's density is split in half, etc.
You could color the lollipops by time-course points, if you're looking to visualize a pattern of where the peak marker lies.
Another option is to go back to the UCSC browser and render the ChIP-seq density tracks in pack or dense display mode. This squishes the peak signals down considerably, which may make it easier to show multiple time-course tracks along with the gene annotation. If you write a custom track, you can apply coloring to various points along the time course.