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The AI Engineer will design and operate agentic workflows for the ReaderSight platform, including LLM integration and automated scoring runs. They are responsible for building prescriptive engines, implementing LLM solutions, and managing automated report generation pipelines.
The AI Engineer builds and operates the agentic workflow that powers ReaderSight — the multi-agent design that harvests signals, triggers alerts, and lets buyers query titles conversationally. This role owns the Claude LLM integration and the automated weekly scoring run end to end.
Build the multi-agent workflow: Signal Harvesting Agent, Scoring Agent, Alert Agent, and Conversation Agent
Implement Agent Bricks orchestration within the existing Databricks environment
Integrate and tune the Claude LLM harness for sentiment, entity, and narrative extraction from messy text and video transcripts
Build the conversational query layer that lets buyers ask plain-English questions about any title or category
Implement threshold-triggered alert generation with per-signal evidence summaries for flagged titles
Build the automated weekly scoring run across all titles with an on-sale date within the 90-day window
Support the backend logic for the Summary UI (ranked list, evidence drill-down, alert dashboard)
Participate in LLM harness and scope testing during UAT
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