AI Solution Architect

The Sr Principal AI Architect is responsible for defining and implementing enterprise‑scale AI solution architecture that enables business teams to operationalize artificial intelligence across critical use cases. This role ensures that AI initiatives are designed with the right architecture, governance, and operational frameworks to move reliably from experimentation to production.

As a strategic technical leader, the Sr Principal AI Architect partners closely with business leaders, product teams, data scientists, engineering organizations, and the enterprise platform architecture team to translate complex business problems into scalable AI‑driven solutions. The role ensures that AI systems are designed for reliability, scalability, governance, and long‑term business impact across the enterprise while aligning with Nutrien’s broader enterprise architecture standards.

What You'll Do:

• 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
• 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

What You'll Bring:

• 10+ years of experience in AI/ML architecture, data science platforms, or advanced analytics solution design
• Demonstrated experience designing and implementing enterprise‑scale AI solutions that deliver measurable business outcomes
• Strong experience with cloud‑based AI platforms such as Azure ML, AWS SageMaker, GCP Vertex AI, or Databricks
• Hands‑on expertise with Python and modern machine learning frameworks such as PyTorch, TensorFlow, or similar ecosystems
• Experience designing ML pipelines and MLOps frameworks using tools such as MLflow, Kubeflow, or similar platforms
• Strong understanding of data platforms, distributed computing, and scalable data processing frameworks
• Familiarity with generative AI architectures including vector databases, RAG pipelines, and LLM orchestration frameworks
• Experience implementing model governance, observability, and lifecycle management practices in enterprise environments
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative discipline

Nutrien is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics.