We present the first work-optimal polylogarithmic-depth parallel algorithm for the minimum cut problem on non-sparse graphs. For for any constant , our algorithm requires work and depth and succeeds with high probability. Its work matches the best runtime for sequential algorithms [MN STOC’20; GMW SOSA’21]. This improves the previous best work by Geissmann and Gianinazzi [SPAA’18] by factor, while matching the depth of their algorithm.