We describe the SurreyCTS system for the BEA 2026 shared task on lexical difficulty prediction. Our approach combines multilingual transformer encoders (RemBERT and COMET) with engineered linguistic features including semantic funnelling, lexical similarity, attention-derived signals, and language-aware representations. A weighted ensemble of the five strongest systems placed fifth among open-track teams, outperforming the open-track baseline across all three learner L1 groups (Spanish, German, and Chinese).