Retrieval Augmented Generation Rag Jobs in Pleasanton, CA

Contribute to architecture, retrieval-augmented generation (RAG) design, prompt engineering, and CI/CD practices that support rapid, reliable delivery of AI features. Succeed in this role by shipping ...

The ideal candidate should have hands-on expertise with Retrieval-Augmented Generation (RAG), Agentic AI workflows, and LLM-based automation, with the ability to integrate AI systems into complex ...

... retrieval-augmented generation (RAG) systems. • Collaborate closely with product and engineering teams to turn early prototypes into production-grade systems. • Help shape the future of AI ...

... RAG (Retrieval-Augmented Generation) models for efficient AI-driven data retrieval. • Implement semantic search and high-speed querying mechanisms for AI-driven insights. • Develop AI-powered ...

Advanced AI/ML: Strong expertise in Large Language Models (LLMs), including techniques like prompt engineering and Retrieval-Augmented Generation (RAG) * Coding Excellence: Proficiency in ...

Familiarity with Large Language Models (LLMs) and Generative AI (GenAI) technologies including Retrieval-Augmented Generation (RAG) and model tuning. * Familiarity with SLMs: model design and fine ...

... retrieval-augmented generation (RAG) systems. • Collaborate closely with product and engineering teams to turn early prototypes into production-grade systems. • Help shape the future of AI ...

Build and scale Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestrations, and API integrations connecting LLMs to internal databases and enterprise software. * Evaluations ...

... retrieval-augmented generation (RAG) systems. • Collaborate closely with product and engineering teams to turn early prototypes into production-grade systems. • Help shape the future of AI ...

Additionally, the candidate will implement Retrieval-Augmented Generation (RAG) models and fine-tune open-source models from leading providers like Meta, Google, Deepseek, and Nvidia. Collaboration ...

Architect and implement Retrieval-Augmented Generation (RAG) pipelines to enhance model performance using external knowledge sources, including document chunking, embedding generation, and retrieval ...

... Retrieval-Augmented Generation (RAG) • Collaborated with AI architects and MLOps teams to ensure Responsible AI, data governance, security, and access controls • Translate complex workflows into ...

Retrieval-Augmented Generation (RAG) architectures * Prompt engineering techniques * Agentic AI workflows and orchestration * Build intelligent systems using frameworks such as LangChain, LangGraph ...

Retrieval-Augmented Generation (RAG) architectures * Prompt engineering techniques * Agentic AI workflows and orchestration * Build intelligent systems using frameworks such as LangChain, LangGraph ...

This role centers on hands-on development of retrieval-augmented generation (RAG) systems, fine-tuning LLMs, and AWS-native microservices that drive automation, insight, and governance in an ...

Architect enterprise-scale Generative AI solutions leveraging LLMs, embeddings, and retrieval-augmented generation (RAG) pipelines. * Design and implement scalable AI microservices and APIs ...

THE ROLE Join our agile team to shape and deliver the industry's premier enterprise Retrieval-Augmented Generation (RAG) platform from the ground up. You will own end-to-end full-stack feature ...

Expertise in conversational AI architectures, agent orchestration harnesses, and Retrieval-Augmented Generation (RAG) for knowledge libraries. * Track record of technical leadership partnering with ...

... RAG - Practical experience implementing retrieval-augmented generation pipelines for context-aware AI applications • MCP (Model Context Protocol) - Practical experience with MCP client/server ...

Hands-on experience building applications that leverage generative AI models, including prompt engineering and retrieval-augmented generation (RAG) * Experience with generative AI research or ...