Temporary Retrieval Augmented Generation Jobs (NOW HIRING)

Prompt engineering, Model evaluation, Retrieval-Augmented Generation (RAG) • Experience working on enterprise-scale or customer-facing systems is a plus. Preferred : • Experience with NLP for ...

Develop LLM-powered applications leveraging Retrieval-Augmented Generation (RAG), tool calling, and orchestration frameworks. * Build scalable APIs, microservices, and integrations supporting ...

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...

Responsibilities : • Design and build scalable and production-grade generative AI systems. • Develop, fine-tune, and evaluate LLMs • Integrate LLMs with Retrieval-Augmented Generation (RAG ...

Build and improve retrieval-augmented generation (RAG) systems with a Senior AI Engineer * Develop chunking and embedding strategies, retrieval-quality processes, and evaluations * Manage context ...

Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions * Hands-on experience with LangChain or similar AI orchestration frameworks * Experience with AWS services such as:

Implement Retrieval-Augmented Generation (RAG) architectures with Oracle Database. * Create and manage vector embeddings and vector indexes. * Integrate Oracle Database with LLMs and Generative AI ...

You will lead Retrieval-Augmented Generation (RAG) and knowledge-retrieval initiatives that support a variety of business functions. You will partner cross-functionally with business leaders, IT ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

Implement conversation memory, tool calling, function execution, and retrieval-augmented generation (RAG) workflows. * Collaborate with product managers, AI engineers, and software developers to ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...

The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI ...