Pairwise sequence alignment is a key component of many bioinformatics workflows and is often a performance bottleneck. Recent advances in sequencing technologies have improved accuracy, while also increasing the need for accelerators that can efficiently handle long reads. Myers’ bit-vector algorithm is well suited to acceleration, and AVX-512 has enabled high-performance implementations, such as SeqMatcher. However, these solutions rely on a fixed register width and AVX-512-specific instructions, which creates a scalability ceiling and limits portability. We implement Myers’ algorithm using RISC-V Vector (RVV) intrinsics and focus on the addition step, which we identify as the main bottleneck in our vectorized kernel. We evaluate two RVV addition alternatives across LMUL values and dataset sizes on a Banana Pi and find that the iterative carry-propagation variant achieves up to 10.29x speedup over the scalar baseline.