Cloud Solutions Architect Ai

We're actively seeking a Cloud Solution Architect (CSA) who specializes in Azure AI services and solutions. As a CSA, you'll be at the forefront of driving our customers' transformation on Microsoft Azure. This customer-facing role involves owning the technical relationship between the customer and Microsoft. Your mission: help customers unlock the full potential of their Microsoft investments through architecture, implementation, and operational health engagements. Plus, we offer flexibility—work remotely up to 50%. Join us in shaping the future of technology 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. **Responsibilities**: **Customer-Centric Approach**: - Understand customers' overall data estate, business priorities, and IT success measures. Innovate with AI solutions that drive business value. - Prioritize Customer Satisfaction: Foster positive relationships and become a trusted advisor. - Ensure Solution Excellence: Deliver solutions with high performance, security, scalability, maintainability, repeatability, reusability, and reliability upon deployment. Gather insights from customers and partners. **Business Impact**: - Drive Consumption Growth: Develop opportunities to enhance Customer Success and help customers extract value from their Microsoft investments. **Technical Leadership**: - Advocate for Customers: Share insights and best practices, collaborate with the Engineering team to address key blockers, and drive product improvements. - Continuous Learning: Stay updated on market trends, collaborate with the AI technical community, and educate customers about the Azure AI platform. - Accelerate Outcomes: Share expertise, contribute to IP creation, and promote reusability to accelerate customer success. **Qualifications**: **Required Qualifications** - Bachelor’s degree in computer science, Information Technology, Engineering, Business or related field with a strong focus on AI - OR equivalent experience. - Several years of 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, with a strong focus on AI - OR equivalent experience. **Preferred Qualifications** - ** Business Value**: The ability to convey the business needs 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. - ** Situational fluency**: 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** - ** 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 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 at the expert level. - Experience in creating AI solutions Proof of Concepts (PoC), and Minimum Viable Products (MVPs) for customers that lead to production deployments. - Competitive Landscape: Knowledge of key AI platforms such as AWS, GCP etc. - Software development practices like DevOps and CI/CD tool chains (i.e., Jenkins, Azure Developer Services, GitHub, MLOps)