Present-day application of metaheuristic algorithms for job scheduling is highly centralized. However, the onset of Industry 4.0 is rapidly changing the manufacturing paradigm from ‘centralized’ to ‘de-centralized’ production through technologies such as Cyber-Physical Systems and Industrial IoT. This mandates the necessity of a new generation of distributed methodologies to perform operations planning. Thus, a novel decentralized algorithm, known as agent-based job scheduling algorithm (ABJS), is proposed in this work to perform scheduling of jobs in a manufacturing flow shop environment. The problem of flow shop scheduling is solved for minimizing makespan under wide-ranging scenarios using machine agents and a scheduling agent. The superior performance of the ABJS algorithm for a high number of jobs signifies its usefulness in real industrial applications.