Seeking a seasoned GenAI and Agentic AI Architect with extensive experience in Microsoft Azure AI services, multi-agent frameworks, LLM orchestration, RAG, Python, and cloud-native engineering. This role is pivotal in architecting secure, scalable, production-ready GenAI solutions, establishing reference architectures, spearheading complex implementations, and fostering enterprise-wide adoption of GenAI and Agentic AI capabilities.

This position offers the opportunity to shape the future of AI within the enterprise, driving innovation and practical application of cutting-edge technologies.

Key responsibilities include architecting comprehensive GenAI and Agentic AI solutions using Azure OpenAI, Azure AI Foundry, Azure Agent Service, Microsoft Agent Framework, Azure Machine Learning, LangGraph, and CrewAI. You will design sophisticated multi-agent systems encompassing planning, reasoning, memory management, state tracking, tool utilization, human oversight, and intricate workflow orchestration.

Further responsibilities involve architecting robust enterprise RAG solutions with Azure AI Search, vector search, Cosmos DB, PostgreSQL pgvector, and Redis. You will also design prompt pipelines, embedding workflows, retrieval strategies, context enhancement, tool integration, model evaluation, and AI guardrails. Building Python microservices with FastAPI or Django, integrating them with Azure AI and enterprise applications, and defining LLMOps and deployment practices using Azure Machine Learning, Azure DevOps, and related services are also critical.

Additionally, you will define architecture standards for security, reliability, scalability, observability, performance, content safety, and cost optimization. Leading architecture reviews, threat modeling, performance benchmarking, prototype development, and ensuring production readiness are essential. You will develop reusable architecture patterns and accelerators, mentor technical teams, and provide architectural guidance for complex GenAI programs.

A minimum of 15 years of technology experience with profound Azure architecture and engineering expertise is required. Candidates must possess strong experience in GenAI, Agentic AI, Azure OpenAI, Azure AI Foundry, Azure Agent Service, Azure Machine Learning, LangGraph, and CrewAI. Expertise in RAG, embeddings, vector databases, multi-agent orchestration, LLMOps, and model evaluation is essential.

Proficiency in Python, particularly with FastAPI or Django, and experience with Azure AI Search, Cosmos DB, AKS, Azure Functions, API Management, Event Grid, and Service Bus are crucial. A strong understanding of Azure security, distributed systems, scalability, performance, and cost optimization is mandatory. An Azure Solutions Architect certification is preferred.