Nitin Shivani
Director Senior Solution Architect @Thomson Reuters
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WORK HISTORY
Director Senior Solution Architect @Thomson Reuters
ON, CA
EDUCATION
RMIT University
Master’s Degree, Computer Engineering
University of Mumbai
B.E., Computer Science
SKILLS
ABOUT NITIN SHIVANI
Technology leader and software architect with nearly 20 years of experience designing and delivering enterprise-grade solutions — from Java/Spring microservices to cloud-native platforms on AWS and GCP.I focus on the intersection of Generative AI, LLMs, and Agentic AI with enterprise systems. I design and build autonomous AI agents and multi-step workflows using foundation models (Gemma, Claude, Bedrock), MCP (Model Context Protocol) tool integrations, and orchestration platforms like n8n and Windmill. From single-shot LLM calls to fully agentic systems that reason, plan, use tools, and execute autonomously — I\'m passionate about making AI practical for businesses, not just prototypes, but production-ready solutions with proper tooling, governance, and human-in-the-loop design.Agentic AI expertise- Designing AI agents that autonomously plan, reason, and execute multi-step tasks - Tool-use patterns: MCP servers, function calling, RAG pipelines, and API orchestration - Human-in-the-loop workflows with suspend/resume, approval gates, and escalation paths - Multi-agent architectures with specialized agents collaborating on complex problems - Bedrock Converse API tool use loop, Claude tool-use, and open-source agent frameworks My background spans the full stack of enterprise architecture- AI & GenAI: LLM agents, agentic workflows, RAG, MCP servers, prompt engineering, Bedrock Converse API - Cloud & Platform: AWS, GCP, Docker, Kubernetes, OpenShift — including leading cloud migrations and.NET modernization/containerization workstreams - Backend: Java/Spring Boot, microservices, event-driven architecture, REST APIs - Architecture: System design, high-level design, domain-driven design, design patterns at scaleI lead teams through complex transformations — whether that\'s migrating monoliths to microservices, containerizing legacy.NET workloads, or introducing agentic AI capabilities into existing enterprise workflows.
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