AI Solutions Engineer

Nucor Business Technology (NBT) is seeking an AI Solutions Engineer to join a new solution engineering team serving Nucors Bar and Engineered Bar Mill Group. The teams charter is to create business value for the Group through technology designing and building the solutions that make Nucor easier to do business with. Digital ordering and commercial capabilities are the first priority but this is a portfolio team by design as business priorities evolve the team redirects its capability to the Groups highest-value opportunity.

You will design build and operate the AI-enabled capabilities in the solutions the team ships: deciding where AI belongs selecting models and integration patterns grounding them in Nucors data and keeping them reliable and safe in production. You will also help define what good looks like for AI-generated output across the teams work the evaluation criteria and the quality practices the team holds itself to as AI-assisted development becomes the way it works by default.

Travel (up to 50%) is expected to support benchmarking knowledge-sharing and internal development sessions at other divisions or NBT hubs.

Candidates must be legally authorized to work in the US (Nucor Business Technology (NBT) will not sponsor the need for a visa now or in the future).

Safety is the most important part of all jobs within Nucor; therefore candidates must be able to demonstrate the ability to initiate lead and uphold safety policies practices procedures and housekeeping standards at all times.

• Design build and operate the AI-enabled components of the teams solutions from model and pattern selection through production.
• Ground AI capabilities in Nucors enterprise data and business rules and integrate them into applications through governed interfaces.
• Define evaluation criteria for AI-generated output and build the methods that verify accuracy reliability and safety both before and after release.
• Establish the teams AI-assisted development practices and quality standards and help the team apply them consistently.
• Partner with business stakeholders and analysts to run discovery surface high-value AI use cases present findings and drive adoption.
• Apply responsible AI practices across the full lifecycle from data handling and access control through ongoing monitoring.
• Build and maintain the data pipelines and integrations that put AI solutions into production.

• Bachelors degree in Computer Science Engineering Information Systems or similar or equivalent practical experience.
• 4 years of experience in a technical role such as Solutions Engineer Software Engineer AI/ML Engineer Systems Analyst or Technical Consultant.
• Proficiency in Python and experience with at least one additional programming language (e.g. JavaScript/TypeScript Java C#).
• Proven ability to design and deploy production applications integrations and data/AI solutions end-to-end including pipelines and operationalization.
• Demonstrated experience building with LLMs or AI services in a production context not limited to prototypes or proofs of concept.
• Working knowledge of enterprise systems APIs and data flows.
• Demonstrated success partnering with non-technical business stakeholders running discovery presenting findings and driving adoption.

• Experience supporting or deploying AI-enabled or advanced analytics solutions.
• Familiarity with AI concepts such as prompt engineering retrieval-augmented generation model evaluation or agent-based workflows.
• Experience with Azure AI services particularly Azure AI Foundry and with identity-based authentication patterns such as managed identity.
• Experience designing formal evaluation methods to measure model or agent output against accuracy reliability and performance criteria.
• Experience creating and using MCP servers.
• Experience with data pipelines and data engineering.
• Experience working in an enterprise IT environment with complex integrated systems.
• Experience integrating with enterprise platforms such as Oracle EBS or similar ERP systems.
• Experience partnering with external vendors or solution providers.
• Background supporting manufacturing supply chain commercial or other enterprise business domains.