…Strong understanding of Retrieval-Augmented Generation (RAG) frameworks, data structures, and how search algorithms function within enterprise knowledge bases. Proven track record managing multi…

…AI architectures, vector search/embeddings, retrieval-augmented generation, and modern analytics platforms — enough to credibly engage technical stakeholders and product teams A track record…

…Experience managing system latency improvements and scalability enhancements. Good understanding of agentic architectures, tool-calling, and Retrieval-Augmented Generation (RAG) grounding layers. Exceptional collaboration…

…for structured and unstructured data using vector databases and Retrieval-Augmented Generation (RAG)-like architectures to power enterprise AI solutions. Experience managing technical discovery…

…Retrieval-Augmented Generation (RAG) pipelines, embedding workflows, vector database integrations and metadata services for enterprise AI applications. Build scalable platform capabilities for managing the…

…memory management, and API integration — ensuring reliability, scalability, and maintainability • Build and optimize Retrieval-Augmented Generation (RAG) pipelines: document ingestion, chunking strategy, embedding, vector…

…power AI agent tool use and retrieval-augmented generation (RAG). - Pre-Production Validation: Guide customers through testing, evaluation, and validation of AI agent performance…

…Generative AI, Agentic AI, Knowledge Graphs, Retrieval-Augmented Generation (RAG), and advanced analytics to improve decision-making, automate workflows, and enhance risk management outcomes…

…and concurrency controls for production AI systems Implement retrieval-augmented generation components where applicable, including chunking, embeddings, retrieval, and grounding strategies Build REST and…

…Fluency in embeddings and vector stores — experienced in building or integrating retrieval-augmented generation (RAG) pipelines, managing vector databases (e.g., FAISS, Pinecone, Chroma…

…tool and function calling, and human-in-the-loop approval patterns Familiarity with GenAI solution patterns such as retrieval-augmented generation, embeddings and vector…

…Senior Engineering Manager to lead the engineering organization responsible for Conversational AI, World Knowledge Question Answering, Retrieval-Augmented Generation (RAG), and Knowledge Intelligence. This…

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

…power their AI products, whether that's vector databases, data pipelines, retrieval-augmented generation (RAG), or fine-tuning workflows - Build and deepen relationships within…

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

…and applied statistics Practical experience with retrieval-augmented generation, including embedding strategies, retrieval quality measurement, and use of vector databases Proficiency operating production workloads…

…and integrations that securely connect legal systems (CLM, matter management, document management, GRC) to large language models and orchestration frameworks. Apply retrieval-augmented generation…

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

…prompt engineering, Retrieval-Augmented Generation (RAG) strategies, and model fine-tuning. Latent Pattern Recognition: Apply advanced ML techniques (e.g., embedding-based clustering, representation…

…of vector databases, retrieval-augmented generation, embedding pipelines - Understanding of AI agent architectures, development patterns, protocols (e.g. MCP, A2A) and multi-agent systems…

…power AI agent tool use and retrieval-augmented generation (RAG). Pre-Production Validation: Guide customers through testing, evaluation, and validation of AI agent performance…

…and ship AI agent applications and agent harnesses that answer business questions accurately over governed data. - Build core agent capabilities, including retrieval-augmented generation…

…orchestration, context management, session handling, and response generation pipelines - Engineer RAG architectures — build and optimize retrievers, vector stores, embedding pipelines, and metadata indexing systems…

…and operational excellence - Experience with generative AI technologies and AI-native development practices, including prompt engineering, LLM integration, agentic architectures, and retrieval-augmented generation…

…and embedding Machine Learning within web applications Experience integrating foundation models, LLM-powered features, retrieval-augmented generation (RAG), or AI agents into production. Experience…