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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Architect - Azure & Cloud AI - **Company:** IBM - **Location:** Chicago, IL, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Continuous Integration, Data Infrastructure, Data Integration, Software Design Patterns, Memory Management, Azure Machine Learning, Enterprise Data Management, Enterprise Software Applications, Azure Data Factory, Large Language Models, Multi-Agent Systems, Prompt Engineering, IT Architecture, Microsoft Fabric, Operational Systems, Machine Learning Operations, Virtual Agents, Azure Synapse Analytics, Software Version Control - **Published:** August 6, 2026 - **Apply:** https://www.juju.com/job/00000000glqs6v ## About the Role Preferred technical and professional experience Preferred Skills * Familiarity with agentic AI frameworks (e.g., LangChain, AutoGen, Semantic Kernel) and RAG architectures * Experience with Azure data services including Azure Synapse, Azure Data Factory, or Microsoft Fabric * Knowledge of AI governance, responsible AI practices, and enterprise security considerations * Azure certifications (e.g., Azure Solutions Architect Expert, Azure AI Engineer Associate) ## Description We are seeking an AI Architect to join our growing AI practice on a high-visibility enterprise engagement. This is a senior, client-facing role where you will provide thought leadership and define the technical direction across a complex, multi-workstream AI program. The client expects a seasoned professional who can hit the ground running - shaping strategy, establishing architecture standards, and driving alignment between business objectives and AI capabilities. You will be the go-to technical authority for end-to-end Azure AI architecture, ensuring that every solution is scalable, secure, governed, and aligned to real business value. What You'll Do Thought Leadership & Technical Direction * Serve as the senior technical voice on the engagement, setting the architectural vision and ensuring consistency across workstreams * Define and govern end-to-end Azure AI architecture spanning Azure OpenAI, Azure Machine Learning, and enterprise data platforms * Develop reference architectures, patterns, and reusable assets that accelerate delivery and elevate the practice * Mentor and upskill team members on Azure AI best practices, design patterns, and emerging capabilities Client Engagement & Solution Architecture * Lead architecture design sessions and workshops with client stakeholders to align on strategy and technical approach * Translate complex business requirements into scalable, secure, and maintainable AI-powered solutions * Map AI use cases to measurable business value, ensuring enterprise standards and governance are embedded from the start * Present architectural recommendations with clarity and confidence to both technical and executive audiences Technical Delivery * Architect and oversee implementation of AI solutions across Azure OpenAI, Azure ML, and supporting data infrastructure * Establish design standards for model deployment, prompt engineering, data integration, and AI observability * Establish a scalable operating model for AI industrialization by standardizing deployment, monitoring, governance, and support processes across existing AI solutions to improve reliability, reuse, and speed to value * Leverage Model Context Protocols (MCPs) to enable secure, modular integration between agents, enterprise systems, and data sources, creating a more interoperable and extensible agentic AI ecosystem * Implement orchestration and guardrail frameworks for agentic workflows to ensure AI agents can collaborate effectively, access the right contextual information, and operate with appropriate oversight, auditability, and human-in-the-loop controls * Ensure all solutions adhere to enterprise security, compliance, and reliability requirements * Collaborate closely with data, engineering, and business teams to ensure successful end-to-end delivery Required technical and professional expertise * 8+ years of experience leading the implementation of enterprise-grade AI and agentic AI solutions across cloud and hybrid environments. * Design scalable AI platforms leveraging Azure and AWS services, including secure model deployment, orchestration, monitoring, and governance. * Build and operationalize LLM-powered applications using frameworks such as LangChain and LangGraph. * Define agentic architectures including multi-agent orchestration, tool calling, memory management, MCP integration patterns, and human-in-the-loop controls. * Establish best practices for AI industrialization, including CI/CD, model lifecycle management, observability, prompt/version management, evaluation frameworks, and guardrails. * Integrate AI systems with enterprise applications, APIs, vector databases, workflow platforms, and operational systems. * Collaborate with business, data, security, and engineering teams to translate business requirements into scalable AI architectures. * Provide technical leadership across architecture reviews, platform strategy, vendor selection, and AI governance initiatives. ## Related Videos - [AI in Leadership: How Technology is Reshaping Executive Roles](https://www.wearedevelopers.com/videos/1705-ai-in-leadership-how-technology-is-reshaping-executive-roles) - [Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure](https://www.wearedevelopers.com/videos/1532-agentic-ai-from-theory-to-practice-developing-multi-agent-ai-systems-on-azure) - [Architectures that we can use with .NET](https://www.wearedevelopers.com/videos/935-architectures-that-we-can-use-with-net) - [Green Cloud Computing](https://www.wearedevelopers.com/videos/592-green-cloud-computing) - [Stop using Node.js like in 2020! 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