AI / ML Engineer

Design & Build AI Solutions

• Translate complex Purchasing business challenges into technically robust AI solutions.
• Design and develop AI/ML applications using Generative AI, Large Language Models (LLMs), traditional ML and emerging AI technologies.
• Build intelligent applications including AI assistants, copilots, autonomous/semi-autonomous agents and AI-powered workflows.
• Develop solutions using APIs, model orchestration, tool calling and enterprise system integrations.
• Rapidly prototype new AI capabilities while maintaining a clear path toward production deployment.

GenAI, RAG & Knowledge Engineering

• Design and implement Retrieval-Augmented Generation (RAG) solutions using structured and unstructured enterprise data.
• Work with vector databases, embeddings, semantic search and hybrid retrieval.
• Design and develop knowledge graphs, context graphs and semantic/knowledge layers where appropriate.
• Develop approaches for connecting relationships across suppliers, categories, contracts, products, locations, transactions and external intelligence.
• Explore and implement Graph RAG and other advanced retrieval and reasoning architectures.
• Develop robust approaches to context engineering, grounding and hallucination reduction.

Machine Learning & Advanced AI

• Develop and deploy machine-learning models for relevant Purchasing use cases such as supplier risk, forecasting, classification, anomaly detection, recommendation and optimization.
• Select appropriate algorithms and AI approaches based on the problem rather than defaulting to a particular technology.
• Design experiments and evaluate model performance using appropriate quantitative and qualitative metrics.
• Apply statistical and machine-learning techniques to extract value from complex enterprise data.

Production Engineering & MLOps

• Take AI solutions from prototype to production.
• Build scalable, reliable and maintainable AI services and applications.
• Implement model and prompt evaluation, monitoring, observability and performance management.
• Establish appropriate approaches for model/version management, testing, deployment, rollback and continuous improvement.
• Design solutions for scalability, latency, reliability and cost efficiency.
• Work with cloud platforms and enterprise AI infrastructure to operationalize AI at scale.

Data & Enterprise Integration

• Work closely with Data Engineers and Enterprise Architects to access and integrate relevant Purchasing data.
• Integrate AI solutions with enterprise platforms such as ERP, procurement, supplier, contract and data platforms.
• Work with both structured and unstructured data.
• Contribute to data preparation, feature engineering, data quality and AI-ready data architectures.
• Design APIs and interfaces that enable AI solutions to interact with enterprise applications and business processes.

Responsible & Secure AI

• Build AI solutions with security, privacy, responsible AI and enterprise controls embedded from the outset.
• Implement appropriate controls around sensitive commercial, supplier and business information.
• Contribute to AI evaluation frameworks covering accuracy, robustness, bias, safety, explainability and reliability.
• Partner with Cybersecurity, Data Privacy, Legal, Risk and Architecture teams to ensure solutions meet enterprise standards.

Technology Leadership & Innovation
 

• Stay current with rapidly evolving developments in GenAI, LLMs, AI agents, ML, knowledge graphs and AI engineering.
• Evaluate emerging models, frameworks, platforms and technologies and determine their relevance to Purchasing.
• Establish reusable AI components, patterns and accelerators that can be leveraged across multiple use cases.
• Contribute to the technical standards, architecture patterns and engineering practices of the Purchasing AI Hub.
• Mentor other engine