Developed cross-project support for the Jais2 Arabic language model, integrating it into the huggingface/transformers, red-hat-data-services/vllm-cpu, and jeejeelee/vllm repositories. Focused on Python-based model development and deployment, the work included implementing LayerNorm and ReLU² activation, modularizing configuration, and expanding documentation and usage examples to streamline adoption. Enhanced testing and quality assurance ensured consistent behavior and compatibility across frameworks, while improvements to modularity facilitated rapid experimentation and performance tuning. The contributions enabled seamless integration of Jais2 into NLP pipelines, supporting both model registry and inference mechanisms, and demonstrated depth in deep learning and natural language processing engineering.