Applied AI Engineer

Nucor•Dallas, TX

1d•Onsite

About The Position

Nucor Business Technology is seeking an Applied AI Engineer for its AI & Emerging Tech Team. The successful candidate will engineer, deploy, and support full-stack AI-driven web applications on enterprise AI platforms such as C3.ai, Palantir Foundry, or similar. The role works directly with stakeholders to design, develop, and operationalize production applications, demonstrations, and proofs of technology, and leads enablement and training initiatives to drive adoption and measurable outcomes. Candidates must be legally authorized to work in the United States; Nucor Business Technology will not sponsor a visa now or in the future. Due to federal security requirements, only U.S. citizens and lawful permanent residents are eligible. Nucor emphasizes safety, and candidates must be able to initiate, lead, and uphold safety policies, practices, procedures, and housekeeping standards at all times.

Requirements

Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related discipline; an equivalent combination of experience and education will also be considered.
At least 3 years delivering AI or ML applications on enterprise platforms, or a relevant degree with strong internships or projects.
At least 1 year of experience with Python, SQL, notebooks, version control, and CI/CD basics.
Working experience operating production pipelines and jobs, including alerting and observability.
Legally authorized to work in the United States; visa sponsorship is not available.
Must be a U.S. citizen or lawful permanent resident due to federal security requirements.
Ability to initiate, lead, and uphold safety policies, practices, procedures, and housekeeping standards.

Nice To Haves

Prior experience with enterprise AI application platforms and their semantic or object models, such as C3.ai model types or Palantir Foundry ontology.
Strong software development background with Python and JavaScript, including modern JavaScript frameworks such as React, Redux, Vue, Backbone, or Angular.
Proficiency with Git or other version control systems.
Experience deploying software to leading cloud platforms such as Azure.
Understanding of SQL and NoSQL databases, data structures, algorithms, and time-series data analysis, including cleansing and normalization.
Working knowledge of Agile software development methodologies.
Strong understanding of common machine learning techniques, applications, and trade-offs.
Experience with data visualization tools such as Power BI, Tableau, or Qlik.
Familiarity with Figma or similar design and prototyping tools for UI/UX collaboration.
Exposure to plant historians, MES, event streams, or edge integrations.
Experience managing continuous improvement projects and implementing supply chain AI applications.
Ability to translate business needs into system requirements and communicate effectively across technical and business teams.

Responsibilities

Build, deploy, and support AI applications and workflows for division, commercial, and corporate teams on enterprise AI platforms.
Stand up proofs of value, validate results quickly, and convert successful solutions into scalable, supportable systems.
Configure, maintain, and support DataOps and MLOps tooling, including pipelines, job orchestration, feature stores, monitoring, and CI/CD.
Create custom AI and machine learning solutions for needs across scrap, EAF, casting, rolling, finishing, logistics, and commercial operations.
Develop and deploy full-stack, AI-based enterprise applications.
Conduct design and development reviews; test, troubleshoot, and enhance software applications.
Deliver technical deep-dives, demonstrations, and internal training.
Create user playbooks and quick-start guides, and conduct enablement and training sessions.
Collaborate with OT, IT, cybersecurity, and business subject-matter experts to meet Nucor requirements for reliability, safety, and compliance.
Work through ambiguity with a hands-on, practical approach in mill environments.
Write application specifications and documentation.
Identify technical risks and gaps and devise mitigation strategies in anticipation of team needs.