5 of 5 Remote Amazon Bedrock Jobs in the North West

and improve retrieval pipelines (embeddings, chunking, hybrid search, ranking, feedback loops), owning schema design, latency, and relevance across vector databases. LLM integration: Connect and orchestrate large language models (OpenAI, Bedrock, etc.), manage prompts, tools, safeguards, and evaluation. Data pipelines: Ingest, clean, and transform structured and unstructured data; design efficient schemas (Postgres/NoSQL) for search and analytics. Frontend (React More ❯

and improve retrieval pipelines (embeddings, chunking, hybrid search, ranking, feedback loops), owning schema design, latency, and relevance across vector databases. LLM integration: Connect and orchestrate large language models (OpenAI, Bedrock, etc.), manage prompts, tools, safeguards, and evaluation. Data pipelines: Ingest, clean, and transform structured and unstructured data; design efficient schemas (Postgres/NoSQL) for search and analytics. Frontend (React More ❯

and improve retrieval pipelines (embeddings, chunking, hybrid search, ranking, feedback loops), owning schema design, latency, and relevance across vector databases. LLM integration: Connect and orchestrate large language models (OpenAI, Bedrock, etc.), manage prompts, tools, safeguards, and evaluation. Data pipelines: Ingest, clean, and transform structured and unstructured data; design efficient schemas (Postgres/NoSQL) for search and analytics. Frontend (React More ❯

and improve retrieval pipelines (embeddings, chunking, hybrid search, ranking, feedback loops), owning schema design, latency, and relevance across vector databases. LLM integration: Connect and orchestrate large language models (OpenAI, Bedrock, etc.), manage prompts, tools, safeguards, and evaluation. Data pipelines: Ingest, clean, and transform structured and unstructured data; design efficient schemas (Postgres/NoSQL) for search and analytics. Frontend (React More ❯

and improve retrieval pipelines (embeddings, chunking, hybrid search, ranking, feedback loops), owning schema design, latency, and relevance across vector databases. LLM integration: Connect and orchestrate large language models (OpenAI, Bedrock, etc.), manage prompts, tools, safeguards, and evaluation. Data pipelines: Ingest, clean, and transform structured and unstructured data; design efficient schemas (Postgres/NoSQL) for search and analytics. Frontend (React More ❯