The Hindu Kush Himalaya (HKH) faces compounding hydroclimatic extremes—GLOFs, monsoonal floods, cloudbursts, and landslide-dam failures—while bridges, dams, roads, and canals expand into narrow, hazard-prone valleys. We propose a translational Earth Observation (EO) framework that replaces stationarity-based planning with dynamic, EO-driven design baselines and embeds satellite analytics at each stage of the infrastructure lifecycle. The framework fuses (i) cryosphere and flood intelligence (lake growth rates, SAR-mapped inundation, sub-seasonal monsoon outlooks), (ii) deformation and slope stability diagnostics from InSAR time series for foundations, abutments, and corridors, and (iii) consequence-led routing and siting linked to exposure and access constraints. We formalise actionable handoffs—EO metrics and thresholds engineered to enter hydrologic models, design load factors, safe-to-fail spillway criteria, and maintenance dashboards—and pair them with governance enablers (interoperability, cross-border data trusts, and capacity pathways for local agencies). Demonstrations across canonical HKH events show how EO chronologies recalibrate return levels, identify failure precursors, and prioritise turn levels, thereby identifying failure precursors and prioritising retrofits. By operationalising EO as a design input—not just a mapping tool—the approach advances climate-smart infrastructure from reactive assessment to anticipatory control, delivering reproducible gains in safety margins and cost-risk tradeoffs for the world’s most fragile mountain corridors.