Sr Software Engineer (4-6 yrs in Python & LangGraph/ LangChain required)

About Gartner IT: Join a world-class team of skilled IT Operation Support Professionals who build the first line of attack for our associates for any of their IT related Support requests or issues and at the same time act as the first line of defense for tier 3 Technical Teams to give them cover for consequences resulted from new upgrades and technology push in the IT environment.  We make a broad organizational impact by delivering cutting-edge technology solutions that power our Associates to achieve our common goal with great efficiency and success.  Gartner IT values its culture of nonstop innovation, an outcome-driven approach to success, and the notion that great ideas can come from anyone on the team. 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 simple 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 efficient 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 a cts safely and accurately when handling sensitive data.   Scale from Concept to Production:  Lead the technical evolution of AI capabilities from experimental POCs to robust, high-availability systems, ensuring the platform scales effortlessly to support thousands of global users.   Optimize   Performance & Cost : Fine-tune LLM interactions and context window usage to balance latency, cost, and response quality, ensuring a seamless real-time experience for Sales and Service users.   Collaborate & Mentor:  Partner closely with Product Managers and Data Scientists to translate high-level business requirements into technical roadmaps, while mentoring junior engineers in best practices for AI application development.   What   you’ll   need: 4–6 years of professional software engineering experience, with a strong   track record   of shipping production-quality code.   Deep   proficiency   in Python application development, including   Fast API,   asynchronous   programming   and performance   optimization .   Hands-on experience building AI applications using orchestration frameworks (specifically   LangGraph  or   LangChain ) and implementing Retrieval-Augmented Generation (RAG) using Vector Databases.   Strong experience designing and deploying scalable solutions on AWS (e.g.,