Agentic AI Architect

Cognizant is one of the world's leading professional services companies, helping organizations modernize technology, reimagine processes, and transform experiences so they stay ahead in a fast-changing world. With over 300,000 associates globally, Cognizant combines a passion for client satisfaction, technology innovation, deep industry and business process expertise, and a global, collaborative workforce that embodies the future of work. We are consistently listed among the most admired companies in the world and among the best companies to work for. Our culture is built on a foundation of transparency, inclusion, and collaboration — empowering our people to grow and thrive both professionally and personally. At Cognizant, you won't just be part of a company; you'll be part of a community that is shaping the future of industries across the globe.

· Azure Agentic AI Architecture: Design and implement scalable, enterprise-grade Agentic AI solutions on Microsoft Azure, leveraging Azure AI Foundry, Azure OpenAI, and Azure Machine Learning with well-defined data flows, component architecture, and resource optimization.

· LLM & RAG Engineering on Azure: Build and optimize LLM-powered applications using Azure OpenAI, implementing advanced Retrieval-Augmented Generation (RAG) pipelines integrated with Azure AI Search and other Azure-native services.

· Multi-Agent Orchestration: Architect and deploy multi-agent systems using Azure ecosystem tools (e.g., Semantic Kernel, orchestration layers), enabling collaborative, goal-driven agent workflows across enterprise use cases.

· Frameworks & Prompt Engineering: Apply deep expertise in frameworks such as Semantic Kernel and LangChain (Azure-integrated), along with advanced prompt engineering techniques to improve model performance, grounding, and response quality.

· Data & Vector Integration: Design integrations with Azure data platforms (Azure Databricks, Azure Synapse) and vector stores (e.g., Azure AI Search vector capabilities), ensuring scalable, efficient embedding and retrieval mechanisms.

· Responsible AI & Governance: Implement Azure-native governance, Responsible AI principles, and compliance controls—including monitoring, model evaluation, security, and risk mitigation frameworks.