Retrieval Augmented Generation Rag Jobs in Arizona

We are looking for a Lead Gen AI Engineer with strong expertise in Python, Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI to lead the design and development of enterprise AI ...

Candidates should have practical experience building GenAI applications using LLMs, Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, AI agents, and enterprise AI governance.

... Retrieval-Augmented Generation (RAG), and Agentic AI technologies. Working within a highly regulated financial environment, you will contribute to building scalable data solutions and support AI ...

... Retrieval-Augmented Generation (RAG), and Agentic AI technologies. Working within a highly regulated financial environment, you will contribute to building scalable data solutions and support AI ...

... Retrieval-Augmented Generation (RAG), and Agentic AI technologies. Working within a highly regulated financial environment, you will contribute to building scalable data solutions and support AI ...

Build intelligent solutions utilizing Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and workflow orchestration technologies. * Develop scalable backend services, REST ...

Build intelligent solutions utilizing Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and workflow orchestration technologies. * Develop scalable backend services, REST ...

... Skills: - Retrieval-Augmented Generation (RAG) - Prompt engineering and optimization - Data Modeling - Synthetic Data Generation - Exploratory Data Analysis - Data cleaning and preprocessing ...

Develop agent-based solutions using modern AI frameworks, Retrieval-Augmented Generation (RAG), GraphRAG, and Model Context Protocol (MCP). * Create and maintain streaming and batch data pipelines ...

... and retrieval-augmented generation (RAG) pipelines that give AI agents access to relevant financial context, including prior work product, regulatory guidance, and client-specific parameters, at ...

Build and implement Agentic AI solutions, including AI agents, orchestration frameworks, and Retrieval-Augmented Generation (RAG) based systems. * Develop, deploy, and support cloud-native ...

Retrieval-Augmented Generation (RAG) * Embeddings, chunking methods, and reranking strategies * Frameworks used to evaluate LLM performance * Tool usage and agent-based architectures * Optimizing ...

Build and maintain content vectorization and retrieval-augmented generation (RAG) pipelines that give AI agents access to relevant financial context, including prior work product, regulatory guidance ...

Build and maintain content vectorization and retrieval-augmented generation (RAG) pipelines that give AI agents access to relevant financial context, including prior work product, regulatory guidance ...

Understanding of Large Language Models (LLMs), generative AI architectures, retrieval-augmented generation (RAG), prompt engineering, vector databases, semantic search, and agentic AI solutions.

Design, build and rollout production-grade AI solutions, including LLM-powered applications, retrieval-augmented generation (RAG) systems, ensuring high standards of accuracy, reliability, and ...

Integrate with large language models (LLMs) using prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) techniques. * Implement MCP client and server within the Grafana ecosystem ...

... Retrieval Augmented Generation (RAG) using vector search and enterprise knowledge sources. • Continuously optimize prompts for accuracy, consistency, latency, and cost efficiency. • Build and ...

Multi-agent architectures Retrieval-Augmented Generation (RAG) pipelines GraphRAG implementations Autonomous agent workflows and orchestration Develop and integrate AI agents with tools, APIs, and ...

LLM APIs (OpenAI / Gemini / Claude) • Prompt engineering Understanding of: • RAG (Retrieval-Augmented Generation) • Embeddings & vector databases Roles & Responsibilities • Experience with ...