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Microsoft Cloud Solution Architect - Data & AI Italy, Lombardy, Milan 517862794
25.06.2024
Qualifications
- Bachelor’s degree in computer science, Information Technology, Engineering, Business or related field AND substantial 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
- Business Value:The ability to convey the business need and value of proposed solutions, plans, and risks to stakeholders and decision makers. This includes the ability to persuade and inform based on facts and alignment with goals and strategy
- Trusted Advisership: The ability to build trusted advisor status and deep relationships across stakeholders (e.g., technical decision makers, business decision makers) through an understanding of customer needs and technologies.
- Situationalfluency: Using self-awareness as a mechanism to interpret verbal and non-verbal cues to increase your ability to "read the room."
- Insightful listening: asking insightful questions to understand the customer needs, issues, business environment and drivers, and going beyond what customer has said
- Technical: Expertise in one or more of the following:
- Experience in delivering large-scale Azure AI Services projects, such as Azure OpenAI, Azure AI Search, Azure Speech, Azure Machine Learning (or equivalent), Generative AI, LLM customization, NLP, MLOps, Evaluation Metrics, Open-source AI frameworks, AI Infrastructure, architecture design.
- Experience creating Data&AI Proof of Concepts (PoC),Minimum Viable Products (MVPs) for customers that lead to production deployments.
- Competitive Landscape: Knowledge of key Data & AI platforms such as AWS, GCP, etc.
- Application development skills – proficient with Python, C#, or similar programming languages in the context of application development, and ability to integrate Azure AI with other services; Deep knowledge ofLLM frameworks (i.e. LangChain, LangGraph, Semantic Kernel, Autogen, etc.)
- Software development practices like DevOps and CI/CD tool chains (i.e., Jenkins, Azure Developer Services, GitHub) and container orchestration systems (i.e., Docker, Kubernetes, Cloud Foundry, Azure Kubernetes Service, GitHub)
Responsibilities
- Customer Centricity
- Understand customers’ overall data estate Business and IT priorities and success measures to design Data & Analytics solutions that drive business value
- Customer Satisfaction - Drive positive Customer Satisfaction & become a trusted advisor
- Ensure that solutionexhibits high levels of performance, security, scalability, maintainability, repeatability, appropriate reusability, and reliability upon deployment
- Customer/Partner Insights -Providefeedback & insights from customers/partners
- Business Impact
- Consumption (Cloud & Support) growth -Develop opportunities to drive Customer Success business results & help Customers get value from their Microsoft investments
- Resolution of Customer Blockers -Identify resolutions to Customer blockers by leveraging SA subject matter expertise. Deliver according to MS best practices & using repeatable Intellectual Property (IP)
- Apply technical knowledge to architect and design solutions that meet business and IT needs, create Data & Analytics roadmaps, drive POCs and MVPs, and ensure long term technical viability of new deployments, infusing key AI technologies where able
- Technical Leadership
- Be the Voice of Customer to share insights and best practices, connect with Engineering team to remove key blockers and drive product improvements
- Learn It All -Maintaintechnical skills and knowledge, keeping up to date with market trends and competitive insights; collaborate and share with the AI technical community while educating customers on Azure platform
- Accelerate customer outcomes - Share expertise
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