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Software Developer Intern AI Tools Team

Arkansas Employer

Mountain Pine, ARInternshipSeen todaySeen in employer's feed today

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At a glance

Compensation
No compensation found
Location
Mountain Pine, AR
Role Type
Internship
Schedule
Internship
Work Authorization
Not specified

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Job overview

The Software Developer Intern will build and maintain production internal tools and AI systems used by WinChoice USA teams. The work includes agent-facing infrastructure, integrations with business systems, and automations and data pipelines. The intern will also participate in requirements conversations to understand business problems before they become specifications.

Skills & qualifications

RequiredNice to have

Skills

Internal Tool DevelopmentMCP ServersTool DefinitionsLLM InfrastructureHubSpot CRMBigQueryMicrosoft GraphAutomationData Pipelines

Full job description

This job was posted by https://www.arjoblink.arkansas.gov : For more information, please see: https://www.arjoblink.arkansas.gov/jobs/4877775 ou'll ship things people actually use. By people, we mean the 400 humans down the hall. Most developer internships hand you a sandbox project nobody will ever run. You build something, you demo it in August, it gets deleted in September. That's not this. WinChoice USA is a 400+ person home improvement company, and our IT team builds its own software. Not scripts; actual internal tools and AI systems that the sales floor, the fulfillment team, and the executives depend on every day. We've built MCP servers that let AI agents query our real business systems. We've built automation that moves data between HubSpot, BigQuery, and a half-dozen SaaS platforms. We've built reporting that the CEO looks at on Monday morning. You'll work on that. The thing you build will be in production, and someone will complain when it breaks. That's the job. What you'll be doing Building internal tools that solve real operational problem, the kind where someone is currently doing something manually and hates it. Working alongside our AI team on agent-facing infrastructure: MCP servers, tool definitions, and the plumbing that lets an LLM do useful work against real data. Integrating with live systems: HubSpot CRM, BigQuery, Microsoft Graph, and whatever else the problem requires. Writing automations and data pipelines that run unattended. Sitting in the requirements conversations, not just receiving a ticket. You'll hear the business problem before it becomes a spec.

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