Engineering large-scale industrial systems mandates an effective Requirements Engineering (RE) process. Such systems necessitate the RE process optimization to align with standards, infrastructure specifications, and customer expectations. However, the current manual execution of RE activities, including but not limited to the identification of requirements from tender documents, finding ambiguous requirements, and allocating them to different teams, is labor-intensive and relies on practitioners’ experience, often leading to project timeline delays. While the effectiveness of current RE practices in developing highly reliable systems across various industries is evident, there is a growing imperative for enhanced support in the RE process. This is because of the evolution of complex modern systems, driven by increased demand for technological advancement to improve efficiency. In this regard, the advent of recent LLMs can significantly augment the RE process and optimize various RE activities to minimize project lead times. We strongly believe that the LLM-augmented RE process is the way forward to address the industry's current needs. Therefore, in this project, we plan to conduct ablation studies involving state-of-the-art open-source LLMs to augment the RE tasks, such as identifying ambiguities in requirements and compliance document explanations.