We run Prometheus in production and this hasn't been our experience at all.
A single machine can easily handle hundreds of thousands of time series, performance is good, and maintaining the alerting rules is a shared responsibility for the entire team (as it should be).
If you use it as a store for all time series data generated by your business, and you want to have indefinite or very-long-term storage, managing prometheus does become a challenge. (hence m3, chronosphere, endless other companies and tech built to scale the backend of prometheus).
IMO, this is a misuse of the technology, but a lot of unicorn startups have invested a lot of engineering resources into using it this way. And a lot of new companies are using it this way; hence the "one engineer's FT job".
After that, we needed some more effort to scale out horizontally with Thanos, but again, once it's set up, it maintains itself.
You can be small with Prometheus and grow into needing an FTE for it - w/o having the migration hurdle of moving out-source to in-source