Description
We are seeking a visionary AI Architect to lead the design and delivery of transformative, enterprise-grade AI solutions. In this role, you will be pivotal in shaping the future of sports, healthcare, and education by architecting and implementing cutting-edge systems. You will translate complex business challenges into robust, scalable AI solutions using platforms like Azure AI Foundry and Google Agent Builder. Your work will involve deep integration with core enterprise systems, including ERP and CRM, ensuring our AI initiatives deliver measurable real-world impact. As a key leader, you will establish AI governance frameworks, championing ethical and transparent practices. You will apply a broad range of techniques, from NLP and computer vision to multi-agent systems, to optimize outcomes and drive innovation. This position requires a strategic thinker with deep technical expertise, capable of defining KPIs and demonstrating the tangible ROI of AI deployments. Join us to build next-generation AI solutions that make a difference.
Requirements
1. Minimum 8 years in solution architecture, with at least 4 years in applied AI/ML.
2. Demonstrated expertise in architecting scalable AI/ML solutions using Azure AI Foundry and/or Google Agent Builder.
3. Proven experience integrating AI systems with enterprise platforms such as ERP, CRM, medical, or sports performance systems.
4. Advanced knowledge of data architecture, including RAG, knowledge graphs, SQL, NoSQL, and vector databases.
5. Hands-on experience applying NLP, computer vision, and predictive analytics to solve business problems.
6. Strong ability to translate complex business cases and requirements into technical AI solution designs.
7. Bachelor’s degree in AI, Data Science, Computer Science, Engineering, or a related field.
8. Experience in implementing governance frameworks for AI transparency, compliance, and ethics.
Desirable
1. Master’s or PhD in a relevant field.
2. Certifications such as Microsoft AI Architect, Azure AI Foundry, or Google Cloud Professional Machine Learning Engineer.
3. Direct industry experience in sports, healthcare, or education.
4. Experience designing and implementing multi-agent systems.
5. Proven track record of defining KPIs, monitoring AI model performance, and tracking ROI.