Solutions Architect

GenAI Ops Solution ArchitectCGI is looking for a Senior GenAI / Agentic AI Engineer to support the migration of an enterprise Knowledge Search/RAG platform from Microsoft Semantic Kernel to Microsoft Agent Framework. The platform is a containerized enterprise RAG solution built using Python/Django, Azure AI Services, and OpenShift. The engineer will be responsible for refactoring the existing Semantic Kernel orchestration layer—including plugins, planners, function calling, prompt templates, memory, and chat history—to the Microsoft Agent Framework agents/workflows model. The role requires strong hands on engineering experience, as migration must preserve existing APIs, security/RBAC, retrieval behavior, citations, and overall RAG quality. This role must be filled on the client site 5 days/week in one of the following locations: Strongsville, OH, Pittsburgh, PA, or Dallas TX.Future duties and responsibilities include: Lead/support migration from Semantic Kernel to Microsoft Agent Framework. Refactor SK Native Plugins, planners, function calling, prompts, memory, and chat history into Agent Framework agents and workflows. Develop and enhance the orchestration layer using Python and Django. Maintain existing API contracts, RBAC, permissions, and application integrations. Integrate with Azure AI Search and Azure OpenAI for hybrid retrieval, semantic ranking, inference, and embeddings. Preserve existing RAG retrieval, reranking, prompt assembly, and citation functionality. Implement tool and connector integrations using Model Context Protocol (MCP). Implement observability using OpenTelemetry and Arize Phoenix. Perform RAG/agent evaluation and regression validation to ensure functional and quality parity after migration. Participate in GitHub based CI/CD, code reviews, DevSecOps, and vulnerability remediation.Required qualifications to be successful in this role include: 8+ years of experience in software engineering, application development, or AI/platform engineering. 4+ years of hands on experience developing enterprise applications using Python, with strong experience in Django based frameworks and APIs. 3+ years of experience designing and implementing Generative AI, RAG, and enterprise AI solutions. Hands on experience with Microsoft Semantic Kernel, including plugins, planners/agents, function calling, prompt templates, memory, and chat history. Hands on experience with Microsoft Agent Framework, including development of agents, workflows, tool integrations, and orchestration patterns. Strong experience migrating or refactoring Semantic Kernel based solutions to Microsoft Agent Framework or equivalent agentic architectures. Strong experience with Azure AI Services, including Azure AI Search, Azure OpenAI, embeddings, hybrid retrieval, semantic ranking, and RAG implementation. Experience implementing Model Context Protocol (MCP) for AI agent tool and connector integrations. Experience deploying containerized Python/AI applications using Docker and OpenShift/OCP. Experience with AI/RAG observability and evaluation frameworks, including OpenTelemetry and Arize Phoenix or similar tools. Experience with GitHub based CI/CD, DevSecOps practices, code reviews, and vulnerability remediation. Working knowledge of Redis Enterprise and Azure API Management (APIM) is preferred.