SVP, AI Deployment & Solution Leader

About the role

The SVP, AI Deployment & Solutions Leader is responsible for driving the organization's AI deployment, solution architecture, and enablement strategy. This executive leader owns and governs the end-to-end AI lifecycle, ensuring AI investments are translated into scalable, secure, and measurable business outcomes.

Responsibilities

• Serve as the organization's senior AI deployment and solutions architecture leader, providing strategic and technical direction on AI platforms, services, models, and implementation approaches.
• Guide business and technology teams in evaluating AI opportunities, selecting the appropriate technologies, and designing scalable AI solutions.
• Establish enterprise architectural standards and reusable design patterns for AI applications, ensuring solutions can scale beyond pilots and proofs of concept.
• Provide expert guidance on Azure AI and AWS AI platforms, including AI Foundry, Azure OpenAI, Azure Machine Learning, Amazon Bedrock, and related services.
• Define and govern a unified enterprise AI technology stack aligned with data, security, governance, and cloud strategies.
• Oversee deployment of highly available, secure, compliant, and resilient AI solutions in production.
• Drive enterprise AI adoption through training, best practices, self-service capabilities, and technical enablement programs.
• Lead and develop a multidisciplinary team of AI architects, ML engineers, platform engineers, data scientists, and technical specialists.

Qualifications

• Master's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related field, or equivalent experience.
• 12+ years of technology leadership experience, including significant experience leading AI, machine learning, cloud architecture, platform engineering, or related functions.
• Deep expertise with Microsoft Azure AI services, including Azure AI Foundry, Azure OpenAI, Azure Machine Learning, and broader Azure cloud capabilities, with Azure serving as the primary enterprise AI platform.
• Strong knowledge of AWS AI services, including Amazon Bedrock, SageMaker, and related cloud-native AI capabilities.
• Demonstrated ability to evaluate, architect, and deploy AI solutions that successfully scale from proof of concept to enterprise-wide production environments.
• Extensive experience providing technical and architectural guidance on AI platforms, solution design, implementation approaches, and operational readiness.
• Strong understanding of enterprise architecture, cloud-native application development, distributed systems, APIs, data platforms, AI infrastructure, and integration patterns.
• Experience establishing MLOps practices, AI governance frameworks, operational standards, and production support models.
• Experience with agentic AI frameworks and technologies, including LangChain, LangGraph, Azure AI Foundry, Amazon Bedrock, and AI capabilities integrated within enterprise software platforms.
• Proven ability to design scalable, reusable, and secure AI architectures that maximize business value while minimizing operational complexity and technical debt.
• Strong executive presence with demonstrated success influencing senior business and technology leaders.
• Proven people leadership experience leading highly technical, multidisciplinary teams.