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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.
Job Responsibility:
Play a pivotal role in the AI Factory, providing technical enablement, operational support, and strategic engagement across customer projects
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 program management utilizing a factory model/approach, driving program awareness and demand across the regional operating units
Attend in-flight project status meetings to monitor progress and identify support needs
Engage directly with complex or non-standard customer use cases beyond existing accelerators
Participate in intake reviews for milestone sizing, objection handling, and technical scoping
Deliver solutions with high performance, security, scalability, maintainability, repeatability, reusability, and reliability upon deployment
Gather insights from customers and partners
Develop opportunities to enhance Customer Success and help customers extract value from their Microsoft investments
Understanding of consumption metrics and their reflection on program effectiveness
Ability to collaborate with local teams for nominations and intake support
Leverage subject matter expertise to identify resolutions for customer blockers
Follow best practices and utilize repeatable IP
Identify and contribute 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
Evaluate pilot opportunities for potential integration into existing offerings
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
Advocate for Customers: Share insights and best practices, collaborate with the Factory team to address key blockers, and influence improvements, roadmap and feature prioritization
Resolve technical blockers: Debug technical issues and provide fixes for engagements encountering blockers
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, drive factory pipeline, and promote Factory to accelerate customer success, as well as collate feedback upon execution to drive improvement and leverage field teams inputs
Embody our culture and values
Requirements:
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
Bachelor's Degree in Computer Science, Information Technology, Engineering, Business, Liberal Arts, or related field AND 8+ 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 consulting OR Master's Degree in Computer Science, Information Technology, Engineering, Business, Liberal Arts, or related field AND 6+ years experience in cloud/infrastructure technologies, technology solutions, practice development, architecture, and/or consulting OR equivalent experience
4+ years experience working in a customer-facing role (e.g., internal and/or external)
4+ years experience working on technical projects
Technical Certification in Cloud (e.g., Azure, Amazon Web Services, Google, security certifications)
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 of the Azure AI specific areas, such as Cognitive Services, Azure OpenAI and CoPilot OR hands-on experience working with the respective products at the expert level
Expertise with Azure AI Search and/or Vector Indexes, Azure Document Processing 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)
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, tools (Jupyter notebooks & VS Code)
Agentic Workflows: Familiarity with Semantic Kernel, 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