Agentic AI & Data Platform Engineering Intern

Hearst•Troy, MI

12h•$20 - $20•Hybrid

About The Position

MOTOR Information Systems is launching a multi-year AI transformation initiative , and we’re looking for a sharp, motivated intern to help us build and modernize the foundations behind it. This is a hands-on internship working with agentic AI workflows and a modern data platform (e.g., Databricks) . If you like turning messy problems into clean, testable solutions, and you don’t panic when the word “agentic” shows up in a sentence- keep reading. Summer 2026 | 11 weeks | 35 hours/week | $20/hour | Remote/Hybrid (as applicable)

Requirements

Undergraduate student (graduation: Summer 2026 )
GPA: 3.6+
Skills/experience with: Python SQL General coding

Nice To Haves

C/C++ or C# (helpful)
Microsoft Excel and Microsoft Word
Data research
A basic understanding of LLMs and modern agentic AI principles

Responsibilities

Support delivery of small, well-scoped modernization initiatives involving agentic AI workflows and a modern data platform
Build and maintain simple data pipelines ( ingest, transform, validate ) using SQL and Python
Assist with prototyping agentic AI use cases (task automation, knowledge retrieval, workflow orchestration) with a focus on safe, testable implementations
Create reusable components (notebooks/scripts) following team standards for naming, structure, and configuration
Implement basic evaluation and testing: unit tests (where applicable), data validation checks, and repeatable run instructions
Practice solid dev hygiene: Git , clear pull requests, requesting code reviews, and issue tracking updates
Produce clear documentation for everything delivered (“what it does,” “how to run it,” “how to troubleshoot it,” known limitations)
Monitor/report on job runs or prototype performance using simple dashboards/logs, flag failures fast with actionable detail
Collaborate asynchronously: daily written updates, ask clarifying questions early, propose next steps when blocked
Follow security/compliance expectations (handle data appropriately, don’t embed secrets, use approved tools/environments)
Take ownership of a defined backlog and deliver incremental results weekly with demos/walkthroughs