With increasing administrative tasks in Higher Education Institutions(HIEs), automation provides an effective solution to improve efficiency. This research introduces an RPA Cognitive Placement Bot that automates resume screening and job matching using Machine Learning (ML) and Natural Language Processing(NLP). The placement bot automatically capture education, skills, and experience from resumes and assesses them with 159 job descriptions acquired from Indeed and LinkedIn. spaCy’s Named Entity Recognition (NER), Selenium, Python-RPA, and Bidirectional Encoder Representations from Transformers (BERT) are employed to expedite the placement process by computing candidate scores through job-resume alignment and sending automated recommendation emails. The bot is trained and tested on 2,006 and 348 resumes respectively with 98.81% training accuracy with BERT, 97.91% with NER, and a net testing accuracy of 99.14%. The proposed virtual bot exhibits outstanding classification efficiency and enhanced performance for HEIs placement automation, when evaluated against current benchmark models —SVM-based (94%), LDA-based (82%), and Decision Tree-based (94%)) proposed by Jagwani et al., (2023) and Prabha et al., (2024).