We are building an enterprise-scale, Azure-native Document Intelligence and Retrieval-Augmented Generation (RAG) platform designed to ingest, classify, extract, enrich, and serve knowledge from large volumes of structured and unstructured data (SharePoint, PDFs, emails, and more). We are seeking a highly skilled MLOps Engineer to operationalize, scale, and govern ML/LLM pipelines across this ecosystem. This role is critical in ensuring the reliability, reproducibility, security, and performance of AI workloads powered by Microsoft Azure and Azure OpenAI Service. Responsibilities: 1. ML/LLM Pipeline Operationalization
Productionize end-to-end pipelines across:
Data ingestion (Graph API, Azure Data Factory)
Document classification (Azure Document Intelligence, LLM-based classifiers)
Data extraction (OCR + LLM parsing)
Data enrichment (embeddings, metadata tagging)
Retrieval (vector and hybrid search)
Build scalable workflows using:
Azure Data Factory
Azure Func...