Overnight Retrieval Augmented Generation Jobs (NOW HIRING)

Your expertise in retrieval-augmented generation will enable the integration of comprehensive data sources, empowering our systems to deliver high-quality, context-aware content and responses. You ...

We are seeking an experienced Engagement Architect with expertise in Agentic AI, Retrieval-Augmented Generation (RAG), and Enterprise AI Architecture . The ideal candidate will lead the architecture ...

We are seeking an experienced Engagement Architect with expertise in Agentic AI, Retrieval-Augmented Generation (RAG), and Enterprise AI Architecture . The ideal candidate will lead the architecture ...

We are seeking an experienced Engagement Architect with expertise in Agentic AI, Retrieval-Augmented Generation (RAG), and Enterprise AI Architecture . The ideal candidate will lead the architecture ...

Develop Retrieval-Augmented Generation (RAG) solutions and AI workflows. Work with Large Language Models (LLMs) such as OpenAI, Azure OpenAI, or similar platforms. Collaborate with product managers ...

This is a Generative AI Engineer / LLM Engineer role with a strong focus on RAG (Retrieval-Augmented Generation), NLP, and Python . They want someone who can: * Build Generative AI applications

Fine-tune foundation models and implement Retrieval-Augmented Generation (RAG) architectures. * Develop REST APIs and microservices using FastAPI, Flask, or similar frameworks to expose AI models.

Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications. * Build and optimize semantic retrieval pipelines, vector search ...

Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications. * Build and optimize semantic retrieval pipelines, vector search ...

The role focuses on Retrieval Augmented Generation (RAG), semantic search, vector databases, metadata engineering, and enterprise knowledge orchestration to deliver secure, accurate, and context ...

Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications. * Build and optimize semantic retrieval pipelines, vector search ...

Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases. * Create AI agents and workflow automation solutions. * Fine-tune, evaluate, and optimize AI models for performance and ...

... Retrieval-Augmented Generation (RAG), and Agentic AI models. Key Responsibilities • Design and architect scalable, maintainable AI solutions that integrate Lang chain, LangGraph, and RAG ...

Working closely with business units, engineers, and functional teams, you will leverage applied AI technologies including large language models (LLMs), retrieval-augmented generation (RAG), AI agents ...

Implement Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs) * Deliver Gen AI use cases in live production environments Required Skills * Python programming ...

Working closely with business units, engineers, and functional teams, you will leverage applied AI technologies including large language models (LLMs), retrieval-augmented generation (RAG), AI agents ...

Design and implement Retrieval-Augmented Generation (RAG) (RAG) pipelines. * Configure and manage open-source vector databases such as Qdrant, Chroma, Milvus, or pgvector. * Generate and manage ...

Implement retrieval-augmented generation (RAG) strategies to enhance the context and relevance of generated outputs. * Manage and optimize vector databases for efficient storage and retrieval of data ...

Design and implement Retrieval-Augmented Generation (RAG) architectures using enterprise data sources. * Integrate AI capabilities into existing Java, .NET, or Node.js enterprise applications.

AI/ML architecture, ML and Generative AI (GenAI) use cases, Large Language Models (LLMs), RAG (Retrieval-Augmented Generation), LangChain, LangGraph,CI/CD for AI pipelines Min experience: 10+ Years