Job Description - AI Engineer

Description

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.



Responsibilities
  • Build prescriptive and optimisation engines using mathematical programming and heuristic solvers
  • Design, develope and implement LLM solutions within secure enterprise infrastructure
  • Engineer LLM prompts to generate plain-language business narratives and ranked recommendations
  • Build automated report generation pipelines delivering structured outputs to business consumers
  • Integrate ML model outputs with generative AI components for consistent and explainable end-to-end delivery
  • Build rule-based trigger engines and exception management workflows
  • Support A/B testing frameworks to compare AI-driven vs. baseline recommendations
  • Design and implement impact analysis and counterfactual simulation capabilities


Qualifications
  • 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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