We are seeking a Data & AI Architect to design build and enable scalable AI and machine
learning solutions within a data-driven platform supporting manufacturing and operational
analytics use cases. This role focuses on building the data and AI foundation for the
Manufacturing Data Hub Analytics Workbench and factory AI Proof of Concept initiatives. The
ideal candidate will bring strong hands-on experience in data platforms machine learning cloudbased AI services and production-ready AI systems supporting enterprise operations. This is a highly technical role (for more senior candidates) that bridges the gap between application teams
and foundational architecture driving platform strategy and enterprise AI enablement.
Required Skills:
Strong experience in Python for AI / ML development
Experience building and deploying ML models in production environments
Experience with LLMs RAG architectures and prompt design
Strong understanding of data pipelines feature engineering and model lifecycle management
Experience with MLOps tools and practices (model deployment monitoring CI/CD for ML)
Hands-on experience with AWS services especially Bedrock
Experience with vector databases such as OpenSearch or Pinecone
Strong understanding of enterprise data platforms and cloud-based data architecture
Proven ability to translate complex technical concepts and bridge the gap between diverse application teams
Preferred Skills:
Familiarity with streaming or real-time data systems
Experience integrating AI solutions into enterprise applications
Exposure to data platforms analytics environments and cloud-native architecture PROTECTED
Experience working across both Data Engineering and AI platform teams
Nice to Have:
Experience in manufacturing automotive industrial or enterprise environments
Exposure to time-series data operational analytics or Industrial IoT environments
Experience supporting factory operations production systems or operational technology platforms
Key Responsibilities:
Design develop and deploy machine learning models for manufacturing and operational use cases
Build solutions such as predictive maintenance anomaly detection quality analytics and operational optimization
Build and maintain end-to-end ML pipelines including data ingestion feature engineering training and inference
Design scalable data architecture supporting AI model development and enterprise analytics
Develop RAG-based applications using AWS Bedrock and vector databases (OpenSearch / Pinecone)
Support the design and enablement of the Manufacturing Data Hub and Analytics Workbench
Integrate AI models into production systems and enterprise applications
Collaborate with Data Engineers and Software teams to ensure scalable and reliable deployments
Contribute to architecture design tool selection platform best practices and AI enablement strategy
Support best practices in model versioning testing deployment and MLOps
Ability to travel up to 10% domestically or internationally within North America
Keywords: AI/ML LLM Jenkins MLOps CI/CD
Job Title: AI Solution Architect/ AI Architect Location: Georgetown KY Duration: 8 Months Job Description: We are seeking a Data & AI Architect to design build and enable scalable AI and machine learning solutions within a data-driven platform supporting manufacturing and operational analytics ...
Job Title: AI Solution Architect/ AI Architect
Location: Georgetown KY
Duration: 8 Months
Job Description:
We are seeking a Data & AI Architect to design build and enable scalable AI and machine
learning solutions within a data-driven platform supporting manufacturing and operational
analytics use cases. This role focuses on building the data and AI foundation for the
Manufacturing Data Hub Analytics Workbench and factory AI Proof of Concept initiatives. The
ideal candidate will bring strong hands-on experience in data platforms machine learning cloudbased AI services and production-ready AI systems supporting enterprise operations. This is a highly technical role (for more senior candidates) that bridges the gap between application teams
and foundational architecture driving platform strategy and enterprise AI enablement.
Required Skills:
Strong experience in Python for AI / ML development
Experience building and deploying ML models in production environments
Experience with LLMs RAG architectures and prompt design
Strong understanding of data pipelines feature engineering and model lifecycle management
Experience with MLOps tools and practices (model deployment monitoring CI/CD for ML)
Hands-on experience with AWS services especially Bedrock
Experience with vector databases such as OpenSearch or Pinecone
Strong understanding of enterprise data platforms and cloud-based data architecture
Proven ability to translate complex technical concepts and bridge the gap between diverse application teams
Preferred Skills:
Familiarity with streaming or real-time data systems
Experience integrating AI solutions into enterprise applications
Exposure to data platforms analytics environments and cloud-native architecture PROTECTED
Experience working across both Data Engineering and AI platform teams
Nice to Have:
Experience in manufacturing automotive industrial or enterprise environments
Exposure to time-series data operational analytics or Industrial IoT environments
Experience supporting factory operations production systems or operational technology platforms
Key Responsibilities:
Design develop and deploy machine learning models for manufacturing and operational use cases
Build solutions such as predictive maintenance anomaly detection quality analytics and operational optimization
Build and maintain end-to-end ML pipelines including data ingestion feature engineering training and inference
Design scalable data architecture supporting AI model development and enterprise analytics
Develop RAG-based applications using AWS Bedrock and vector databases (OpenSearch / Pinecone)
Support the design and enablement of the Manufacturing Data Hub and Analytics Workbench
Integrate AI models into production systems and enterprise applications
Collaborate with Data Engineers and Software teams to ensure scalable and reliable deployments
Contribute to architecture design tool selection platform best practices and AI enablement strategy
Support best practices in model versioning testing deployment and MLOps
Ability to travel up to 10% domestically or internationally within North America