Cloud Solution Architect - Azure AI / Machine Learning

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. 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.

This role is flexible in that you can work up to 100% from home.

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.

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. You will also drive product influence with Engineering through technical feedback and increase technical intensity with the Field teams. This opportunity will allow you to accelerate your career growth, honing your technical and programme management skills, and deepening your cloud expertise.

Responsibilities

Customer-Centric Approach:

• Understand customers'' overall data estate, business priorities, and IT success measures.
• Innovate with AI solutions that drive business value.
• Facilitate scalable delivery through strong technical programme management utilizing a factory model/approach; driving programme awareness and demand across the regional areas.
• Ensure Solution Excellence: Deliver solutions with high performance, security, scalability, maintainability, repeatability, reusability, and reliability upon deployment. Gather insights from customers and partners.

Business Impact:

• Drive Consumption Growth: Develop opportunities to enhance Customer Success and help customers extract value from their Microsoft investments.
• Unblock Customer Challenges: Leverage subject matter expertise to identify resolutions for customer blockers. Follow best practices and utilize repeatable IP.
• Build repeatable IP and assets that create velocity in deployment and drives customer value from their Unified investment. Continuously look to improve upon these assets utilizing the best of field inputs.
• Architect AI Solutions: Apply technical knowledge to design solutions aligned with business and IT needs. Create Innovate with AI roadmaps, lead POCs and MVPs, and ensure long-term technical viability.

Technical Leadership:

• Advocate for Customers: Share insights and best practices, collaborate with the Engineering team to address key blockers, and influence product improvements, roadmap and feature prioritization.
• Continuous Learning: Stay updated on market trends, collaborate with the AI technical community, and educate customers about the Azure AI platform.
• Accelerate Outcomes: Through engaging with field teams, share expertise, contribute to IP creation, and promote reusability to accelerate customer success, as well as collate feedback on assets to drive improvement and leverage field teams inputs.

Qualifications

Required/Minimum Qualifications:

Bachelor's degree in computer science, Information Technology, Engineering, Business or related field AND 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.

Domain Expertise in Azure AI Areas:Deep domain expertise in one of the Azure AI specific areas, such as Cognitive Services, Machine Learning, Azure OpenAI and CoPilot OR hands-on experience working with the respective products at the expert level.

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:

Core AI & ML Concepts: Familiarity with AI & ML foundational knowledge of concepts like Prompt Engineering, compute systems (GPU & FPGA), popular frameworks (TensorFlow & PyTorch), and tools (Jupyter notebooks & VS Code).

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.

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.

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, Kubernetes, Docker, API Management).

DevOps and MLOps: Strong understanding of DevOps practices and CI/CD tool chains, and familiarity with MLOps (AI & ML lifecycle management) for sustainable enterprise grade deployments.

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

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