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Iceberg calving and near-shore landslides in Greenland produces seiches in the fjords - standing tsunami-like waves on the order of minutes of period that resonate for hours (or even days in extreme cases, see Svennevig et al., 2024), and can pose danger to the population and cause damage to infrastructure in the villages. For more than a decade, it has been known that broadband seismic sensors on-shore are sensitive to the ground tilt induced by these waves (Amundsen et al., 2012). Seiches are typically seen in seismic data as very long period waves that last tens of minutes to hours. This means that a network of on-shore seismic sensors can be employed to provide a tsunami early warning (TEW) system for both on-site and network-wide TEW. A major advantage of seismic networks over pressure gauges is the fact that the sensors are not exposed to the destructive forces of sea ice and icebergs, which are abundant in many regions of Greenland. In this work we demonstrate how a seismic network in the Uummannaq fjord (Greenland) can be used to provide TEW to the villages in the fjord. We further demonstrate an algorithm that allows detecting seiches and discriminating them from other sources of long-period signals (mostly large teleseismic earthquakes). Such an algorithm, however, can be significantly affected by corrupted data (spikes, steps, etc.), which produce false alarms. We then demonstrate how we can remove these false triggers using a deep scattering network (Seydoux et al., 2020). Our results show that we can detect seiches with little false alarms and provide timely TEW in the Uummannaq fjord, including the 2017 Nuugatsiaq landslide. We also demonstrate our implementation of the developed TEW algorithm into a real-time system in SeisComP.