The unified Rwandan initiative for national ZEBOVAC immunization (UMURINZI) program's community engagement component was enacted to mobilize and vaccinate high-risk community members. This article describes best practices and lessons learned from the implementation of UMURINZI, a large-scale Ebola vaccination program. The population deemed to be at risk for EVD consisted of people who frequently cross Rwanda and the Democratic Republic of Congo (DRC) borders including those coming from Kigali City, potential first responders who have not previously been vaccinated against EVD, as well as people who reside in high-risk border-proximate areas of the Rubavu and Rusizi districts in the Western Province of Rwanda. These districts were selected because of their proximity to high-traffic borders linking Rwanda to DRC's cities near an active Ebola outbreak. Volunteers of this program were adults, adolescents, and children aged 2 years or above who resided in the selected communities. Recruitment at the sites was conducted in close collaboration with each health area's Community Health Workers (CHWs). Volunteers were informed that the program involved being fully vaccinated (two doses of Ebola vaccines) within 2 months apart in the allocated vaccination sites. Lessons learned were categorized into four pillars: infrastructure, leadership, myths, and partnership with respect. The best practices that were used during the implementation of the UMURINZI program were the results of a collaboration among CHWs, the involvement of national and local leaders, the use of a comprehensive engagement plan, and training. The study also had limitations. We described best practices and lessons learned during the implementation of the UMURINZI program in Rwanda. These practices and lessons learned represent promising options that could contribute to better community members' participation in mass vaccination programs. Hence, we demonstrated that rigorously designed community awareness and sensitization programs are effective for the implementation of similar programs in resource-limited settings.