Retrieval Augmented Generation Rag Jobs in Rochester, MI

We are seeking an experienced AI/ML Architect to design and develop conversational AI solutions using Retrieval-Augmented Generation (RAG) techniques. The ideal candidate will have a strong ...

... Retrieval Augmented Generation (RAG) solution. The ideal candidate should be capable of working across the full AI lifecycle, including ingestion, retrieval, modeling, APIs, testing, deployment ...

The AI Architect will own and define reference architectures for Retrieval-Augmented Generation (RAG), Conversational AI, Document Intelligence, and Agentic AI, ensuring solutions are scalable ...

Experiment with and implement Retrieval Augmented Generation (RAG), embeddings, vector databases, and other AI-driven architectures * Create seamless full-stack experiences from database to user ...

Solid understanding of Prompt engineering and retrieval-augmented generation (RAG), RESTful APIs and integration patterns, and Data structures, algorithms, and basic ML/LLM concepts. * Experience ...

Solid understanding of Prompt engineering and retrieval-augmented generation (RAG), RESTful APIs and integration patterns, and Data structures, algorithms, and basic ML/LLM concepts. * Experience ...

... RAG (Retrieval-Augmented Generation) systems to enhance agent knowledge and context Create generative models for code generation, content creation, and strategic planning within agent frameworks ...

Experience building LLM-powered APIs or retrieval-augmented generation (RAG) systems. * Knowledge of vector databases (e.g., Pinecone, Weaviate, FAISS, OpenSearch kNN). * Experience with Kafka ...

Experience building LLM-powered APIs or retrieval-augmented generation (RAG) systems. * Knowledge of vector databases (e.g., Pinecone, Weaviate, FAISS, OpenSearch kNN). * Experience with Kafka ...

Experience building LLM-powered APIs or retrieval-augmented generation (RAG) systems. * Knowledge of vector databases (e.g., Pinecone, Weaviate, FAISS, OpenSearch kNN). * Experience with Kafka ...

Retrieval-Augmented Generation (RAG) systems * Internal AI services and APIs * Integrate commercial and open-source LLMs (e.g., OpenAI, Anthropic, Databricks, open-source models) into enterprise ...

Exposure to LLM application patterns such as retrieval-augmented generation (RAG), prompt engineering, or evaluating AI output quality. * Hands-on usage of AI tools in your development workflow, such ...

Exposure to LLM application patterns such as retrieval-augmented generation (RAG), prompt engineering, or evaluating AI output quality. * Hands-on usage of AI tools in your development workflow, such ...

Retrieval, grounding & context engineering Develop end-to-end Retrieval-Augmented Generation (RAG) pipelines: ingestion, chunking, embeddings, vector and hybrid retrieval, reranking, contextual ...

Experience with LLM application patterns such as retrieval-augmented generation (RAG), agent evaluation harnesses, guardrails, or production monitoring of AI behavior. * Strong hands-on usage of AI ...

Experience with LLM application patterns such as retrieval-augmented generation (RAG), agent evaluation harnesses, guardrails, or production monitoring of AI behavior. * Strong hands-on usage of AI ...

... RAG (Retrieval-Augmented Generation): Deep, practical knowledge of building and optimizing RAG pipelines. This includes data ingestion, various chunking strategies, embeddings, vector databases (e.g ...

... and retrieval-augmented generation. * Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces ...

Experience with retrieval-augmented generation (RAG), vector databases, embeddings, and grounding models in enterprise data. * Familiarity with prompt engineering, context engineering, fine-tuning ...

Exposure to technologies or patterns such as Model Context Protocol (MCP), LangChain, retrieval-augmented generation (RAG) patterns, vector databases, AI agents, or evaluation frameworks * Experience ...