Enterprise AI Solution Architecture

• Lead the architecture and design of AI-powered solutions that address strategic business challenges across Nutrien’s operations, supply chain, commercial, and digital platforms
• Translate business use cases into scalable AI architectures that integrate data, machine learning, and modern application frameworks
• Define architectural patterns and reference architectures for building production-grade AI applications
• Guide teams in selecting appropriate AI techniques including predictive modeling, optimization, and generative AI to deliver measurable business value
• Ensure AI solutions are designed with scalability, resilience, and enterprise integration in mind

AI Platform and MLOps Architecture

• Define architectural standards for the end-to-end AI lifecycle including data preparation, model development, deployment, monitoring, and continuous improvement
• Establish enterprise patterns for MLOps and ModelOps including CI/CD for ML pipelines, model versioning, experiment tracking, and automated deployment
• Partner with data engineering teams to ensure AI workloads are supported by scalable and reliable data platforms
• Architect reusable components such as feature stores, model registries, evaluation frameworks, and model monitoring capabilities
• Enable teams to transition successfully from experimentation and prototypes to production-grade AI systems

Generative AI and Advanced AI Systems

• Design architectures for modern AI applications that leverage large language models, retrieval-augmented generation (RAG), and vector-based knowledge systems
• Define patterns for integrating generative AI into enterprise workflows and applications
• Establish architectural guidance for AI copilots, intelligent automation, and decision-support systems
• Evaluate emerging AI technologies and recommend approaches that align with enterprise strategy and security requirements

AI Governance and Responsible AI

• Establish architectural standards for model governance, explainability, observability, and lifecycle management
• Collaborate with risk, compliance, and security teams to embed responsible AI principles into enterprise AI solutions
• Define best practices for traceability, data lineage, model performance monitoring, and operational oversight
• Ensure AI solutions align with enterprise data governance and security standards

Enterprise Architecture Alignment

• Collaborate closely with the Platform Architecture and Enterprise Architecture teams to ensure AI solutions align with enterprise technology standards, integration patterns, and cloud architecture principles
• Ensure AI implementations leverage approved enterprise platforms, shared services, and architectural frameworks wherever possible
• Contribute to the evolution of enterprise architecture standards related to AI, machine learning, and generative AI technologies
• Help define reusable architectural blueprints that enable consistent and scalable implementation of AI capabilities across business domains

Leadership and Cross-Functional Collaboration

• Serve as a strategic advisor to business and technology leaders on AI architecture and implementation approaches
• Provide architectural oversight for high-impact AI initiatives from concept through production deployment
• Mentor data scientists, ML engineers, and solution architects on modern AI system design and operationalization practices
• Drive adoption of enterprise AI standards, reusable frameworks, and architectural best practices across teams
• Foster innovation by identifying opportunities where AI can unlock new capabilities or transform business processes