…Experience building pipelines for structured, unstructured data, incorporating vector databases and retrieval-augmented generation (RAG)-like architectures to power enterprise-grade AI solutions. Preferred…

…integrating next-generation AI (Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic workflows) into daily operations, modernizing legacy enterprise middleware, and driving data…

…Key development areas will include the Linux (Android) kernel, device drivers, embedded firmware, Android userspace daemons, performance analysis, and Linux power management. You will…

…Join our innovative team and shape the future of software development with AI-driven solutions. — Implement retrieval-augmented generation (RAG) pipelines, prompt engineering strategies…

…Working knowledge of generative artificial intelligence building blocks, including large language models, prompt design, retrieval augmented generation, context design, evaluation methods, and safety controls…

…embedded builder who bridges the gap between frontier Artificial Intelligence (AI) products and production-grade reality within customers. You will manage blockers to production…

…This work includes embeddings, shared feature layers, unified models, ranking systems, and behavioral understanding that support retrieval, ranking, ads, and personalized experiences across Pinterest…

…AgentCore, and SageMaker) to set up secure, private-network AI environments, and practical experience implementing Retrieval-Augmented Generation using embeddings, vector stores, and semantic…

…production GenAI features, and solve hard problems at the intersection of knowledge graphs, multi-agent orchestration, LLM-powered personalization, and retrieval-augmented generation - all…

…Build scalable systems that use large language models, retrieval-augmented generation, embeddings, semantic search, knowledge graphs and related AI techniques to support security scenarios…

…Hands-on experience with modern Generative AI platforms (AWS Bedrock, OpenAI, Anthropic, etc.). Deep understanding of retrieval-augmented generation (RAG), embeddings, and knowledge-base…

…AgentCore, and SageMaker) to set up secure, private-network AI environments, and practical experience implementing Retrieval-Augmented Generation using embeddings, vector stores, and semantic…

…AgentCore, and SageMaker) to set up secure, private-network AI environments, and practical experience implementing Retrieval-Augmented Generation using embeddings, vector stores, and semantic…

…AgentCore, and SageMaker) to set up secure, private-network AI environments, and practical experience implementing Retrieval-Augmented Generation using embeddings, vector stores, and semantic…

…agent tool discovery and invocation. - Hands-on experience with retrieval-augmented generation (RAG), vector databases, and knowledge base configuration for production AI systems. - AWS…

…deployment patterns including retrieval-augmented generation (RAG), fine-tuning decision frameworks, knowledge base configuration, vector database selection, and chunking/embedding strategies. Cross-Functional & Go…