Engineering LLMOps: Building Robust CI/CD Pipelines for LLM Applications on Google Cloud

The transition of large language models (LLMs) from experimental notebooks to production-grade applications requires more than just a well-crafted prompt. As enterprises integrate generative AI into their core workflows, the need for stability, scalability, and reproducibility becomes paramount. This is where LLMOps — the intersection of DevOps, Data Engineering, and machine learning — enters the frame. Building a CI/CD pipeline for LLM-based applications on Google Cloud Platform (GCP) presents unique challenges.