Microsoft Cloud Solution Architect CSA - Azure AI & Machine Learning 

United States 

977670053

As a
Cloud Solution Architect (CSA) - Azure AI & Machine Learning

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.

• DevOps and MLOps: understanding of DevOps practices and CI/CD tool chains, and familiarity with MLOps (AI & ML lifecycle management) for sustainable enterprise grade deployments.
• Core AI & ML Concepts: Familiarity with AI & ML foundational knowledge of concepts like Prompt Engineering, compute systems (GPU & FPGA), popular frameworks (TensorFlow & PyTorch), and tools (Jupyter notebooks & VS Code).
• 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.
• Landscape: Understanding the landscape is valuable, candidates should be aware of key AI platforms beyond Azure, such as AWS and GCP. Knowledge of the AI open-source ecosystem.

Required/Minimum Qualifications

• 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.

Additional or Preferred Qualifications

• Bachelor's Degree in Computer Science, Information Technology, Engineering, Business, 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

o OR Master's Degree in Computer Science, Information Technology, Engineering, Business, or related field AND 6+ years experience in cloud/infrastructure technologies, technology solutions, practice development, architecture, and/or consulting

o 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.
• 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, Machine Learning, Azure OpenAI and CoPilot OR hands-on experience working with the respective products.
  • 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, Kubernetes, 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.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:Microsoft will accept applications for the role until July 15, 2024.

• Understand customers'' overall data estate, business priorities, and IT success measures.
• Innovate with AI solutions that drive business value.
• Facilitate scalable delivery through technical program management utilizing a factory model/approach; driving program awareness and demand across the regional areas.
• Ensure Solution Excellence: Deliver solutions with high performance, security, scalability, maintainability, repeatability, reusability, and reliability upon deployment. Gather insights from customers and partners.

• Drive Consumption Growth: Develop opportunities to enhance Customer Success and help customers extract value from their Microsoft investments.
• Unblock Customer Challenges: Leverage subject matter expertise to identify resolutions for customer blockers. Follow best practices and utilize repeatable IP.
• Build 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.
• Architect AI Solutions: 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.
• Stakeholder Management. Excellence in executive stakeholder management across Field and Corp organizations through effective communications, delivery of actionable insights, and hands-on support on key engagements to enable successful execution
• Operational Excellence. Operationalization with weekly and monthly rhythms to activate execution at scale with Field and partner teams
• Business Thought Leadership. Strategy definition and management for Accelerating ACR through the CMF delivery model for Scale segments and Partner channels

• Advocate for Customers: Share insights and best practices, collaborate with the Engineering team to address key blockers, and influence product improvements, roadmap and feature prioritization.
• 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, contribute to IP creation, and promote reusability to accelerate customer success, as well as collate feedback on assets to drive improvement and leverage field teams inputs.

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