Temporary 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 ...

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 ...

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

Skilled in Retrieval-Augmented Generation (RAG), FAISS, vector databases, Transformers, BERT, Hugging Face. Frameworks & APIs: Strong with LangChain framework, REST APIs, Git, CI/CD, Kubernetes.

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 ...

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 ...

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 ...

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

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 ...

The ideal candidate will have experience in prompt engineering, AI agentic frameworks, large language models (LLMs), retrieval-augmented generation (RAG), and vector databases. This role requires a ...

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