AI Engineer

Job-: IT

Location:

Columbus, OH, United States

Schedule:

Full time Posted:
At Worthington Enterprises, we are not just experimenting with AI—we are embedding it into how we operate, make decisions, and create value for our customers.

We are looking for a hands-on, forward-thinking AI Engineer to transform governed enterprise data into impactful business solutions. You will build and deploy AI-powered applications, agents, predictive models, and intelligent workflows that help people work more efficiently, make better decisions, and improve operational performance. This is an opportunity to shape reusable enterprise AI patterns, tackle meaningful manufacturing and business challenges, and see your solutions progress from idea to measurable impact.

This hybrid role is based in Columbus, Ohio, and requires at 2 to 3 days per week on-site. Occasional travel—approximately 10%—to corporate and manufacturing locations may be required. This position is not eligible for relocation assistance or U.S. work sponsorship. What You'll DoDesign, build, deploy, and improve AI applications including enterprise agents, retrieval-augmented generation (RAG), natural-language analytics, predictive models, and workflow automations.

Build Snowflake-native AI and ML solutions using capabilities such as Cortex Agents, Cortex Search, semantic views and structured-data tools, Cortex AI functions, Snowpark, Model Registry, and Feature Store where appropriate.

Engineer retrieval and context pipelines for structured and unstructured data, including ingestion, chunking, metadata, hybrid search, citations, permissions, and freshness.

Create reliable agentic workflows in n8n or comparable orchestration platforms, incorporating tool calling, human approval, retries, idempotency, secrets management, auditability, and exception handling.

Develop secure integrations with Microsoft 365, SharePoint, Teams, enterprise APIs, databases, file sources, and Model Context Protocol (MCP) tools.

Establish evaluation and monitoring practices for answer quality, task completion, drift, safety, latency, cost, adoption, and business value.

Apply software engineering practices including modular design, automated testing, code review, Git-based delivery, CI/CD, documentation, and production support.

Partner with business teams to frame opportunities, prototype quickly, translate ambiguity into a delivery plan, and guide adoption of solutions that are useful and trusted.

Contribute reusable patterns, standards, and guardrails that help other teams and AI Champions build responsibly.

Continuously evaluate new models and capabilities, separating durable value from short-lived hype.

What We're Looking For Bachelor’s degree in computer science, data science, engineering, information systems, or a related field—or equivalent practical experience.

Typically 3–5 years of relevant experience in AI/ML engineering, software engineering, data engineering, or data science, including evidence of delivering at least one AI-enabled solution beyond a one-off prototype.

Strong Python and SQL skills, plus experience with APIs, source control, testing, and maintainable application or pipeline development.

Hands-on experience with one or more of the following: LLM applications, RAG, tool-using agents, natural-language analytics, ML pipelines, or intelligent automation.

Understanding of data modeling, identity and access control, privacy, secure development, and responsible AI principles.

Ability to evaluate AI system quality systematically and diagnose failure modes rather than relying on anecdotal testing.

Strong collaboration and communication skills, including the ability to explain tradeoffs to both technical and business partners.

Preferred Qualifications Snowflake AI/ML…