We describe the MohannadHendi submission to the AraGenre 2026 shared task. The system casts hierarchical Arabic genre classification as cross-lingual retrieval between Arabic texts and English genre definitions, allowing it to consider labels unseen during training. We fine-tune multilingual E5-large on 140 texts paired with five deterministic views of their genre definitions. At inference, the nearest normalized definition embedding supplies both the broad and specific labels. The best local configuration achieved 0.9020 specific Macro F1. The submitted system obtained 0.4560 Hierarchical Macro F1 and ranked eighth among 18 final leaderboard entries. Its broad Macro F1 (0.6125) exceeded its specific Macro F1 (0.2995), showing that fine-grained genre discrimination remains the main difficulty.