Position Title: Manufacturing AI Solution Architect
Location: Georgetown, KY (Hybrid/Onsite as required)
Start Date: June 15, 2026
Duration: 10+ Months
Pre-Screening Questions - Do you have strong hands-on experience with Python for AI/ML development?
- Have you built, deployed, and maintained machine learning models in production environments?
Position Overview We are seeking an experienced
Data & AI Architect to design, build, and enable scalable Artificial Intelligence and Machine Learning solutions within a data-driven platform supporting manufacturing and operational analytics initiatives.
This role will be instrumental in establishing the AI and data foundation for the
Manufacturing Data Hub,
Analytics Workbench, and factory AI Proof-of-Concept (PoC) programs. The ideal candidate will possess deep technical expertise in data platforms, machine learning, cloud-based AI services, and enterprise-grade AI systems.
This is a highly technical, senior-level position that serves as a bridge between application development teams and enterprise architecture, driving AI platform strategy, governance, and adoption across the organization.
Required Skills & Experience - Strong proficiency in Python for AI/ML development
- Proven experience building, deploying, and supporting machine learning models in production environments
- Hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and prompt engineering
- Strong understanding of data pipelines, feature engineering, and ML lifecycle management
- Experience implementing MLOps practices, including model deployment, monitoring, CI/CD, and version control
- Hands-on experience with AWS AI services, particularly AWS Bedrock
- Experience working with vector databases such as OpenSearch and Pinecone
- Strong knowledge of enterprise data platforms and cloud-based data architecture
- Demonstrated ability to communicate complex technical concepts and collaborate across diverse application and engineering teams
Preferred Qualifications - Experience with real-time or streaming data architectures
- Experience integrating AI/ML solutions into enterprise applications
- Familiarity with modern data platforms, analytics ecosystems, and cloud-native architectures
- Experience collaborating across Data Engineering and AI Platform teams
Nice-to-Have Experience - Manufacturing, automotive, industrial, or large-scale enterprise domain experience
- Exposure to time-series data, operational analytics, or Industrial IoT (IIoT) environments
- Experience supporting factory operations, production systems, or Operational Technology (OT) platforms
Key Responsibilities - Design, develop, and deploy machine learning solutions for manufacturing and operational use cases
- Build AI-driven applications including predictive maintenance, anomaly detection, quality analytics, and operational optimization
- Develop and maintain end-to-end ML pipelines covering data ingestion, feature engineering, model training, deployment, and inference
- Design scalable data architectures that support AI model development and enterprise analytics initiatives
- Develop Retrieval-Augmented Generation (RAG) applications leveraging AWS Bedrock and vector databases (OpenSearch/Pinecone)
- Support the architecture and enablement of the Manufacturing Data Hub and Analytics Workbench
- Integrate AI models into production systems and enterprise applications
- Collaborate with Data Engineering and Software Development teams to ensure reliable, scalable deployments
- Contribute to platform architecture, tool selection, governance, and AI best practices
- Implement and promote best practices in model versioning, testing, deployment, monitoring, and MLOps
- Support enterprise AI enablement initiatives and long-term platform strategy
- Travel up to 10% domestically and internationally (North America) as business needs require
Candidate Submission Requirements Please provide:
- Updated Resume (Word Format)
- Work Authorization Copy (H1B, EAD, or Green Card, if applicable)
Candidate Information - First Name (as per Passport):
- Last Name (as per Passport):
- Phone Number:
- Email Address:
- LinkedIn Profile:
- Current Location (City, State):
- US Work Authorization:
- Willing to Relocate (Yes/No):
- Last 4 Digits of SSN:
- Date of Birth (MM/DD):
- Availability/Start Date:
- Corp-to-Corp (Yes/No):
- Expected Lowest All-In Hourly Rate:
- Open to Hybrid Work Model (Yes/No):
- Willing to Travel up to 25% (Yes/No):
