Cloud Solution Architect
Encontrado en: Talent CO C2 - hace 2 semanas
Overview
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 For Data &AI part of to Spanish South America (SSA) organization, you will customers in 8 countries to achieve their outcomes based on their investments in Microsoft technology. Leveraging your Microsoft Azure Artificial Intelligence (AI) and Machine Learning (ML) and all the Data Analytics 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 collaboration skills, and deepening your cloud expertise.
The SSA Data & AI team is responsible for the strategy, design, and implementation of Microsoft’s end-to-end customer experience. Come join SSA Data & AI 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 a differentiated and connected customer experience.
Qualifications
Required/Minimum Qualifications
Required/Minimum Qualifications
· Bachelor's Degree in Computer Science, Information Technology, Engineering, Business, or related field AND 7+ 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
o OR equivalent experience.
Additional or Preferred Qualifications
Breadth of technical experience and knowledge (preferred): Application development skills – proficient with Python, Java, or similar programming languages in the context of application development, and ability to integrate Azure AI with other services; cloud application deployment experience with services such as Azure Functions, Kubernetes, Docker, API Management, and related Architecture Design – the ability to create and explain 3-tier architecture diagrams, system context diagrams, system interaction diagrams, etc. Experience in architecting deployments for production in an enterprise setting including infrastructure knowledge, security, networking, and other considerations. 4+ years experience working on technical projects in a customer-facing role (e.g., internal and/or external) Ability to build relationships, orchestrate, lead, and influence virtual teams, ensuring successful acceleration and unblocking of customer projects Technical Certification in Cloud (e.g., Azure, Amazon Web Services, Google, security certifications) Presentation and communication skills with a high degree of comfort with key audiences (Senior Executives, Management, Data Scientists, Engineers, etc.) Accelerate new customer opportunities from Proof of Concept (PoC) to Production for Azure AI & Data Analytics portfolio workloads such as Azure OpenAI, Azure Cognitive Search, and Azure Machine Learning, SQL, Databricks, Fabric and others. Provide customers with Generative AI expertise and advisory through architecture designs, proof of concepts, production reviews, and post-sales support. Expand and grow Azure AI & Analitycs solutions adoption for existing customer base. Lead and provide guidance in technical escalations to unblock customers in collaboration with Microsoft stakeholders. Provide expert perspective to key stakeholders to increase platform adoption through customer insights & feedback on a regular basis. Drive product improvement and influence roadmap with Engineering through deep technical insights. Increase AI & Data analytics technical intensity in the field through upskilling, sharing best practices, and scaling repeatable IP.-
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