Pairwise alignment of short DNA sequences with affine-gap scoring is a common processing step performed in a range of bioinformatics analyses. Dynamic programming (i.e. Smith-Waterman algorithm) is widely used for this purpose. Despite using data level parallelisation, pairwise alignment consumes much time. There are faster alignment algorithms but they suffer from the lack of accuracy.In this paper, we present MEM-Align, a fast semi-global alignment algorithm for short DNA sequences that allows for affine-gap scoring and exploit sequence similarity. In contrast to traditional alignment method (such as Smith-Waterman) where individual symbols are aligned, MEM-Align extracts Maximal Exact Matches (MEMs) using a bit-level parallel method and then looks for a subset of MEMs that forms the alignment using a novel dynamic programming method. MEM-Align tries to mimic alignment produced by Smith-Waterman. As a result, for 99.9% of input sequence pair, the computed alignment score is identical to the alignment score computed by Smith-Waterman. Yet MEM-Align is up to 14.5 times faster than the Smith-Waterman algorithm. Fast run-time is achieved by: (a) using a bit-level parallel method to extract MEMs; (b) processing MEMs rather than individual symbols; and, (c) applying heuristics.MEM-Align is a potential candidate to replace other pairwise alignment algorithms used in processes such as DNA read-mapping and Variant-Calling.