I have a data set that looks like this
id name year job job2
1 Jane 1980 Worker 0
1 Jane 1981 Manager 1
1 Jane 1982 Manage
I think this does what you want, although the data must be sorted as you have presented it.
my.df <- read.table(text = '
id name year job job2
1 Jane 1980 Worker 0
1 Jane 1981 Manager 1
1 Jane 1982 Manager 1
1 Jane 1983 Manager 1
1 Jane 1984 Manager 1
1 Jane 1985 Manager 1
1 Jane 1986 Boss 0
1 Jane 1987 Boss 0
2 Bob 1985 Worker 0
2 Bob 1986 Worker 0
2 Bob 1987 Manager 1
2 Bob 1988 Boss 0
2 Bob 1989 Boss 0
2 Bob 1990 Boss 0
2 Bob 1991 Boss 0
2 Bob 1992 Boss 0
', header = TRUE, stringsAsFactors = FALSE)
my.seq <- data.frame(rle(my.df$job)$lengths)
my.df$cumu_job2 <- as.vector(unlist(apply(my.seq, 1, function(x) seq(1,x))))
my.df2 <- my.df[!(my.df$job=='Boss' & my.df$cumu_job2 != 1),]
my.df2$cumu_job2[my.df2$job != 'Manager'] <- 0
id name year job job2 cumu_job2
1 1 Jane 1980 Worker 0 0
2 1 Jane 1981 Manager 1 1
3 1 Jane 1982 Manager 1 2
4 1 Jane 1983 Manager 1 3
5 1 Jane 1984 Manager 1 4
6 1 Jane 1985 Manager 1 5
7 1 Jane 1986 Boss 0 0
9 2 Bob 1985 Worker 0 0
10 2 Bob 1986 Worker 0 0
11 2 Bob 1987 Manager 1 1
12 2 Bob 1988 Boss 0 0