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Responsibilities (Text Only)
- Accelerate new customer opportunities from Proof of Concept (PoC) to Production for Azure AI workloads such as Azure OpenAI, Azure Cognitive Search, and Azure Machine Learning
- 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 adoption for existing customer base.
- Lead and provide guidance in technical escalations to unblock AI 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 technical intensity in the field through upskilling, sharing best practices, and scaling repeatable IP
- Other: Embody our culture and values
Qualifications (Text Only)
Required/Minimum Qualifications
- Bachelor's degree in computer science, Information Technology, Engineering, Business, or related field AND proven 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 equivalent experience.
- Proven years' experience with enterprise-scale technical delivery experience with Azure AI Services including Azure OpenAI, Azure Cognitive Search, Azure Speech, Azure Machine Learning (or equivalent), Generative AI, LLM customization, NLP, Search, MLOps, Open-source AI frameworks, AI Infrastructure, architecture design.
- Proven years' experience creating AI Proof of Concepts and Minimum Viable Products (MVPs) and supporting production deployments.

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.
- Proven 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.)

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

Cloud Solution Architect - Azure AI and Machine Learning