Senior Cloud Solution Architect

With over 17,000 employees worldwide, the mission of the Customer Experience & Success (CE&S) organization is to empower customers to accelerate business value through differentiated customer experiences that leverage Microsoft’s products and services, ignited by our people and culture. Come join CE&S and help us build a future where customers achieve their business outcomes faster with technology that does more.  

The Global Customer Success (GCS) organization is leading the effort to create the desired customer experience through support offer creation, driving digital transformation across our tools, and delivering operational excellence across CE&S.   

As a Cloud Solution Architect aligned to the Azure AI platform for Microsoft's Customer Experience & Success (CE&S) organization, you will enable customers to achieve their outcomes based on their investments in Microsoft technology. Leveraging your Microsoft Azure Artificial Intelligence (AI) and Machine Learning (ML) technical subject matter expertise, you will lead technical conversations with customers and Microsoft colleagues, driving value to their organization. This is a hands-on role that includes accelerating customer adoption by building Generative AI solutions and identifying resolutions to unblock customer success projects for the AI Factory. You will also drive product influence with Engineering through technical feedback via the Factory and increase technical intensity with the Field teams. This opportunity will allow you to accelerate your career growth, honing your technical and program management skills, and deepening your cloud expertise.  

The Microsoft Customer Experience & Success (CE&S) organization is responsible for the strategy, design, and implementation of Microsoft’s end-to-end customer experience. Come join CE&S and help us build a future where customers come to us not only because we provide industry-leading products and services, but also because we provide differentiated and connected customer experience.  

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.  

CSAs are senior individual contributors who operate globally and engage directly with customers. It is a hands-on technical role spanning across design, build, and production with a focus on issue resolution to remove customer production blockers. Candidates are expected to comfortably switch from a whiteboard to the keyboard. This is a truly exciting role that will feature unique and challenging technical problems to solve and to help our customers succeed.

Required/Minimum Qualifications  

• Bachelor’s degree in computer science, Information Technology, Engineering, Business or related field AND 4+ years’ experience in cloud/infrastructure technologies, information technology (IT) consulting/support, systems administration, network operations, software development/support, technology solutions, practice development, architecture, and/or Business Applications consulting
  • OR equivalent experience.  

Other Qualifications

• Microsoft is unable to sponsor a work visa for this role due to the nature of the role’s job duties. 

Additional or Preferred Qualifications  

Breadth of technical experience and knowledge in foundational security, foundational AI, architecture design, with depth / Subject Matter Expertise in one or more of the following:   

• Deep Domain Expertise in Azure AI Areas: Deep domain expertise in one or more of the Azure AI specific areas, such as Cognitive Services, Azure OpenAI, AI Agents, Microsoft Foundry and Copilot Studio OR hands-on experience working with the respective products at the expert level. Expertise with Azure AI Search and/or Vector Indexes, Azure Document Intelligence, Azure Content Understanding and /or equivalent OCR technology  
• Programming Languages and Integration: Proficient with Python, C#, R, JavaScript, or similar programming languages in the context of application development, and ability to integrate Azure AI with other services (e.g., Azure Functions, Azure Container Apps, Docker, API Management, MCP servers). 
• Architecting Enterprise-Grade Solutions: The ability to create and explain 3-tier architecture diagrams, system context diagrams, system interaction diagrams, etc.  
  Proven experience building enterprise-grade, AI-focused solutions on the cloud (Azure, AWS, GCP) for customers, from Minimum Viable Products (MVPs) leading to production deployments. 
• Infrastructure as Code (IaC) Deployment: Strong understanding of Bicep, Terraform, or Azure Resource Manager and familiarity with configuration and deployment of IaC templates in a secure environment.
• Core AI & ML Concepts:  Familiarity with AI & ML foundational knowledge of concepts like Prompt Engineering, RAG, Agentic Orchestration, tools (Jupyter notebooks & VS Code). 
• GenAIOps & DevOps: Familiarity with CI/CD pipelines (GitHub Actions, Azure DevOps), Prompt and Model Evaluation, AI Harnesses (e.g., evaluation, orchestration), and observability for general Azure workloads using Application Insights, Azure Monitor, OpenTelemetry and/or other Observability tools.
• Agentic Workflows: Familiarity with Agent Framework, MCP, Langchain, or other agentic frameworks. Ability to configure tools for dynamic execution by an LLM
• Generative AI and Responsible AI: Knowledge of current and emerging AI technology, including Generative AI technology applications and use cases (including, but not limited to, Large Language Models) and Foundational models toolsets. 
• Understanding of Responsible AI practice including ethical considerations, bias mitigation, and fairness. 
• Competitive Landscape: Understanding the competitive landscape is valuable, candidates should be aware of key AI platforms beyond Azure, such as AWS and GCP. Knowledge of the AI open-source ecosystem