About this role:
Join our Agentic AI Applications team to build the next generation of Gartner’s Sales and Service Delivery enablement tools. In this role, you will architect a sophisticated Agentic AI ecosystem designed to act as a force multiplier for our associates, moving beyond straightforward chatbots to create context-aware digital partners. You will drive the development of a comprehensive intelligent digital assistant capable of "connecting the dots" between client initiatives, value delivery, past engagements & interactions, and our vast library of expert research. You will engineer solutions that leverage Retrieval-Augmented Generation (RAG), multi-agent orchestration, secure intent recognition and effective context handling—ensuring our Sales and Service teams have a powerful, intelligent interface to navigate critical business data and be more productive and effective in their client interaction preparation and follow up workflows.
What you’ll do:
Architect & Build Agentic Systems: Design and implement scalable, multi-agent architectures that autonomously retrieve,
synthesize, and act upon complex data sets—including client intelligence, strategic priorities, and historical engagement & Interactions logs.
Develop Advanced RAG Pipelines: Engineer robust Retrieval-Augmented Generation (RAG) solutions that aggregate diverse business intelligence—spanning strategic client priorities, communication history, and value metrics—to ensure the AI possesses a holistic, real-time understanding of the client relationship.
Orchestrate Complex Workflows: Build the logic that "connects the dots" across disparate systems, enabling the digital assistant to hand off tasks to specialized sub-agents or external APIs.
Ensure Enterprise-Grade Reliability: Implement rigorous guardrails, security controls, and intent recognition layers to ensure the AI acts safely and accurately when handling sensitive data.
Scale from Concept to Production: Lead the technical evolution of AI
📌 Sr Data Engineer Gurugram (India)
🏢 Gartner
📍 India