Retrieval Augmented Generation Rag Jobs in Snoqualmie, WA

Retrieval-Augmented Generation (RAG) ? AI Agent Development Client Requirements: ? FAANG, Product Companies, or Tier-1 Companies experience is Mandatory.

You will design, implement, and ship LLM-powered agent tools, MCP integrations, and retrieval-augmented generation (RAG) systems that are already in production use and you will do it using AI ...

You will design, implement, and ship LLM-powered agent tools, MCP integrations, and retrieval-augmented generation (RAG) systems that are already in production use and you will do it using AI ...

What You'll Do Build production AI systems Design and deliver the core services that power enterprise document understanding, retrieval, knowledge grounding, and Retrieval-Augmented Generation (RAG ...

What You'll Do Build production AI systems Design and deliver the core services that power enterprise document understanding, retrieval, knowledge grounding, and Retrieval-Augmented Generation (RAG ...

... RAG (Retrieval-Augmented Generation) techniques. • Strong understanding of natural language processing (NLP). Experience with data preprocessing and model fine-tuning. • Familiarity with ...

You will design, implement, and ship LLM-powered agent tools, MCP integrations, and retrieval-augmented generation (RAG) systems that are already in production use and you will do it using AI ...

Develop and operationalize RAG (Retrieval-Augmented Generation) pipelines integrating LLMs (e.g. Claude, Gemini, GPT-4) into production privacy applications. * Implement structured prompting ...

Build advanced retrieval-augmented generation (RAG) systems including vector databases, embedding strategies, chunking optimization, hybrid search, re-ranking, and multi-source data synthesis

... RAG (Retrieval-Augmented Generation) techniques. • Strong understanding of natural language processing (NLP). Experience with data preprocessing and model fine-tuning. • Familiarity with ...

Design and implement Retrieval-Augmented Generation (RAG) solutions leveraging enterprise knowledge, business data, and structured information sources. * Build and orchestrate AI agents using modern ...

Architect and implement the foundational platform for Agentic and classic AI, encompassing model orchestration, retrieval-augmented generation (RAG), memory systems, and Agent-to-Agent (A2A ...

Architect and implement the foundational platform for Agentic and classic AI, encompassing model orchestration, retrieval-augmented generation (RAG), memory systems, and Agent-to-Agent (A2A ...

... Retrieval-Augmented Generation (RAG) systems and LLM-based solutions to enhance financial knowledge retrieval and decision support Proactively identify and solve challenges related to GenAI solutions ...

Familiarity with retrieval-augmented generation (RAG), vector databases, and enterprise AI architectures preferred. * Demonstrated ability to influence technical strategy across cross-functional ...

Architect retrieval-augmented generation (RAG) and computer vision pipelines that interpret plan sets, generate takeoffs, and surface contextual insights. * Combine LLMs, CV, and rule-based logic to ...

Architect and implement the foundational platform for Agentic and classic AI, encompassing model orchestration, retrieval-augmented generation (RAG), memory systems, and Agent-to-Agent (A2A ...

... Retrieval-Augmented Generation (RAG) systems and LLM-based solutions to enhance financial knowledge retrieval and decision support Proactively identify and solve challenges related to GenAI solutions ...

Hands-on experience with LLM frameworks and patterns (LangChain, LlamaIndex, Semantic Kernel), vector databases, and Retrieval-Augmented Generation (RAG) architectures. * Experience with MLOps/LLMOps ...

Hands-on experience with AI productivity tools (Claude and Cursor or similar IDE) and working knowledge of foundation models, prompt engineering, retrieval-augmented generation (RAG), and AI agent ...