AI Engineering Intern Spring 2026

Teknor Apex Company•Pawtucket, RI

About The Position

When Alfred Fain founded a small Rhode Island tire store in 1924, at the time no one could have predicted how Teknor Apex would become an international custom compounder sought out by companies around the world. After a nearly hundred-year journey that's carried us through acquisitions and expansion, we now have nine U.S. locations, as well as operations in Belgium, Singapore, Germany, and China. Throughout this global expansion Teknor has remained a privately held company, and today Fain's grandson sits at the helm, maintaining the family's tradition of fostering deep employee and customer relationships. These relationships are what allow us—together—to deliver customized compound solutions and help our customer's create better products. “Manufacturing is a team sport and we work together to achieve our goals.” ~Jon Fain Join the team behind our custom compounds. In this role as an IT Intern you will develop an understanding of best practices in enterprise integration, process automation, and reusable component design. You will learn how modern workflow orchestration tools (like n8n, Make, or Retool) connect with complex business systems such as Infor M3 ERP, CRMs, and data platforms. By the end of the internship, the student will have contributed tangible assets—such as integration components, documentation, and reference materials that improve Teknor Apex's automation ecosystem. Duties include: Essential Duties and Responsibilities:

Requirements

Pursing a degree in Business, Computer Science or Mathematics or any other STEM major
Junior or Senior academic standing preferred.
Familiarity with modern workflow and automation tools such as n8n, Make (Integromat), or Retool.
Basic understanding of APIs, data integration, and enterprise systems (ERP, CRM, or data platforms).
Experience with or coursework in programming/scripting languages (e.g., Python, JavaScript, or SQL.
Exposure to system design principles, particularly related to modularity, reusability, and scalability.
Strong analytical and problem-solving abilities; able to translate complex business processes into structured workflows.
Excellent written and verbal communication skills for creating clear technical documentation and collaborating with diverse teams.
Self-motivated and curious about emerging automation, integration, and AI technologies.

Responsibilities

Documenting and structuring business rules and data to help automate compound orders in the M3 ERP system. Their work will focus on turning expert knowledge and scattered information into reusable, well-organized materials that support system automation and can serve as templates for future projects.
The intern will help document, organize, and publish the foundational “building blocks” that make up Teknor Apex's enterprise automation platform. Their work will focus on turning technical standards, reusable agents, and integration patterns into clear, usable references that help developers and analysts build reliable automations faster.
Help design and develop reusable integration components—code-based connectors and utilities—that allow enterprise systems (such as M3 ERP, CRM, and data platforms) to plug seamlessly into modern automation and AI workflow tools like n8n, Make, or Retool. The work blends software engineering with systems integration, focusing on making complex enterprise data and processes accessible to low-code and AI-driven automations.
1-2 functional reusable connectors implemented and demonstrated in at least one automation platform.
Documentation or reference assets (e.g., quick-start guide, pattern description, or integration example) published for internal reuse.
Hands-on experience gained in API integration, workflow automation, and the principles of scalable, maintainable system design.
Practical collaboration with technical and business stakeholders, including participation in sprint reviews, testing, and architecture discussions.
A final presentation or demo summarizing the intern's deliverables, lessons learned, and recommendations for extending their work.

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