Survival Analysis Code in R

#1
A few years ago I used the following SAS code to perform survival analysis for the purpose of predicting when someone would retire from my company.

proc lifereg data=survive.combined2;
model Years_of_Service*censor(1) = Unemployment_Rate Pension_Plan Newhire Veteran Disabled Female Full_Time Component Salary Education/ DIST=weibull ;
output out=New cdf=Prob predicted=pred_years_of_service q=0.90;
run;

Line 3 of this code (the output and the predicted commands) allowed me to generate the estimated values (for each observation in my sample) for my dependent variable in the form of a new variable called pred_years_of_service. So (if a couple of other conditions were met), if the value of Years_of_Service for observation number 1 in my sample was 20 years, and the value of Pred_Years_Of_Service for that same observation was 23 years, it is save to conclude (with a probability of at least 90%) that the person in question will retire in 3 years.

How do I do the same thing in RStudio? How do I replicate in RStudio the SAS code above and more specifically how do I generate a new data set that contains the predicted values of my dependent variable so I can subtract them from it and generate an estimate for when the people who are predicted to retire will do so?