AI Engineer

Zensar Technologies; Maharashtra; On-site; INR 1,800,000 - 3,500,000; Full time

Job summary

Zensar Technologies is seeking an AI Engineer to build and operate the agentic workflow powering ReaderSight, with Claude LLM integration and automated weekly scoring end to end. The role focuses on developing prescriptive engines, LLM solutions, and pipeline automation within secure enterprise infrastructure.

The engineer will craft prompts, integrate model outputs with AI components, and build trigger and analytics capabilities to deliver explainable, data-driven recommendations to business

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

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

Job description

Job 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.

Job 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

About Us

At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus.

Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.

We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.