AI-Enabled Manufacturing Solutions Lead

EY; San Mateo (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

EY in the United States is seeking a Solution Manager in Supply Chain Manufacturing Operations to design, build, test, and scale AI-enabled manufacturing solutions, blending domain knowledge with data platforms and RAG workflows.

You will create prototypes, reference architectures, and reusable components, collaborating with engineers, data scientists, and solution leaders to turn priority use cases into production-ready assets.

Qualifications

• Experience designing AI-enabled manufacturing solutions for industrial environments.
• Ability to translate manufacturing problems into AI use cases and requirements.
• Strong knowledge of data platforms, knowledge graphs, and DataOps concepts.
• Proven ability to develop prototypes, demos, and reusable components.

Responsibilities

• Own end-to-end AI manufacturing solution development and scaling.
• Translate problems into clearly defined AI use cases, user stories, and requirements.
• Lead prototypes from concept through working demo and handoff for industrialization.
• Design data platform architectures connecting MES/MOM, ERP, historians, SCADA, PLC, IoT.
• Develop reusable data models and knowledge graphs across assets and processes.
• Design RAG solutions with embeddings, vector search, and grounding.
• Build AI assistants, copilots, and workflows for manufacturing use cases.
• Create reference implementations and demonstrations for pursuit and delivery teams.

Skills

AI-enabled solutions

Solution design

Manufacturing domain

Data platforms

Knowledge graphs

RAG

MLOps

Agile development

API integrations

Data modeling

Tools

MES/MOM

ERP

SCADA

PLC

IoT

Data pipelines

Cloud platforms

Job description

EY in the United States is seeking a Solution Manager in Supply Chain Manufacturing Operations to design, build, test, and scale AI-enabled manufacturing solutions, blending domain knowledge with data platforms and RAG workflows.

You will create prototypes, reference architectures, and reusable components, collaborating with engineers, data scientists, and solution leaders to turn priority use cases into production-ready assets.