About the Role

The Cloud Solution Architect role is a senior technical position focused on designing and implementing AI-driven cloud solutions for customers. Responsibilities include architecting AI applications, resolving production blockers, and driving consumption growth through technical leadership. The role requires deep expertise in Azure AI services, cloud architecture, and enterprise-grade solution deployment.

Key Responsibilities

• Architect AI Applications & Solutions aligned with business and IT needs
• Unblock customer challenges by leveraging subject matter expertise to resolve production blockers
• Drive consumption growth by developing opportunities to enhance customer success and value from Microsoft investments
• Advocate for customers by sharing insights and collaborating with engineering teams to influence product improvements
• Build repeatable IP and assets to accelerate deployment and drive customer value

Required Skills & Qualifications

Must Have:

• Bachelor's Degree in Computer Science, IT, Engineering, Business, or related field AND 4+ years experience in cloud/infrastructure technologies, IT consulting/support, or related areas
• 2+ years experience working in a customer-facing role
• Experience with cloud/infrastructure technologies, architecture, and/or consulting
• Ability to work in the U.S. without visa sponsorship (Microsoft cannot sponsor for this role)

Nice to Have:

• Bachelor's Degree AND 8+ years experience OR Master's Degree AND 6+ years experience in cloud/infrastructure technologies, architecture, or consulting
• 4+ years experience working in a customer-facing role
• 4+ years experience working on technical projects
• Technical Certification in Cloud (e.g., Azure, AWS, Google, security certifications)
• Deep domain expertise in Azure AI areas like Cognitive Services, Machine Learning, Azure OpenAI, or CoPilot
• Proficient with Python, C#, R, JavaScript, or similar programming languages
• Proven experience building enterprise-grade AI solutions on cloud platforms (Azure, AWS, GCP)
• Strong understanding of DevOps practices, CI/CD tool chains, and MLOps
• Familiarity with AI & ML foundational concepts like Prompt Engineering, GPU/FPGA, TensorFlow, PyTorch, Jupyter notebooks, VS Code
• Knowledge of current and emerging AI technology, including Generative AI, LLMs, and Responsible AI practices
• Understanding of competitive AI platforms (AWS, GCP) and the AI open-source ecosystem

Benefits & Perks

• Industry leading healthcare