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 setting
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

📌 Ai Engineer Pune
🏢 Zensar Technologies
📍 Pune