This role requires a practitioner who has operated inside or directly alongside engineering and product organizations-someone who has personally led SDLC transformations, managed engineering teams, governed AI coding tool rollouts, or run DevOps programs at scale-and who can translate that hands-on operating experience into rapid, credible impact within the compressed timelines of a PE holding period. Govern LLMOps at enterprise scale: RAG pipeline architecture and optimization (chunking strategies, embedding models, vector database selection-Pinecone, Weaviate, Qdrant, pgvector), prompt versioning, evaluation frameworks (RAGAS, LangSmith, Phoenix), and inference cost governance.