Embedded AI Experience, Micro-Frontend and SDK The goal is to build a reusable conversational and analytics experience that can be integrated into products owned by other teams. The UI must receive authentication, active screen context, filters and user actions from the host product, then display streamed answers, tables, charts, citations and conversation history. The integration approach may use a micro-fronted, Web Component, embedded SDK, module federation or secure iframe; experience embedding and operating a UI service within another application is the key requirement. Minimum capabilities Strong React and TypeScript production experience Proven experience embedding a UI, service or micro-frontend within another application Experience designing clean integration APIs, SDK contracts, callbacks, events and versioned interfaces Experience capturing host-application context such as the active page, filters, selected objects and user actions Experience building streaming, multi-turn GenAI interfaces with clarification flows, conversation history and error handling Experience rendering structured responses, including tables, charts, citations and reusable results Experience integrating REST and streaming APIs, authentication and token management Preferred Experience building reusable UI SDKs or components used by multiple host applications Experience with micro-frontends, Web Components, module federation or secure iframe patterns Familiarity with MCP clients, embedded analytics or enterprise copilot products Familiarity with AWS, Amazon Bedrock and AgentCore-backed applications
