Senior Software Engineer - Retrieval-Augmented Generation (RAG) at Elsevier

Elsevier is looking for a seasoned software engineer with five or more years of experience who has moved beyond general backend work into the world of production-scale RAG systems. You should be someone who can comfortably navigate the entire lifecycle of LLM applications, from document ingestion and vector database management to fine-tuning retrieval quality. **What makes it worth a look...** The compensation is transparent, reaching up to $171,954 for New Jersey residents, and includes an annual incentive bonus. It is a rare chance to build high-stakes AI tools for the healthcare sector within a stable, world-renowned research publishing giant that provides a full suite of local benefits. **You might be a good fit if you...** * Have built and operated end-to-end RAG pipelines using Python or NodeJs. * Work regularly with vector databases, embedding strategies, and reranking models. * Understand MLOps workflows including model versioning, feature stores, and CI/CD for AI. * Experience with agentic tools like LangGraph or performance monitoring via platforms like MLflow.