Ai Engineer Internship at Rebel Athletic in Carrollton, TX

Summary: Rebel Athletic is a fast-growing cheer and performance wear brand that focuses on building confidence and empowering performance. They are looking for an AI Engineer Intern to design and deploy AI systems that automate workflows and drive business outcomes across various departments. Responsibilities: - Work directly with the Technology team to design and deploy AI solutions into production environments - Build AI agents that automate real business processes - Turn complex workflows into structured, multi-step AI systems - Work hands-on with Python, LLMs, APIs, and modern AI frameworks - Use tools such as LangChain, CrewAI, n8n, or similar - Integrate AI into platforms like NetSuite, Salesforce, and internal tools - Rapidly prototype, test, and iterate on solutions - Partner with business teams to identify high-impact automation opportunities Required Qualifications: - Experience building AI agents through projects, internships, or research - Strong Python skills and familiarity with AI or ML tools - Experience working with LLMs and APIs - Ability to take a business problem and turn it into a working solution - Strong problem-solving skills and systems thinking mindset - Demonstrated ownership and ability to move quickly and independently - Class of 2027 undergraduate or graduate student in Computer Science, Engineering, Data Science, Business Analytics, AI, or a related field - Curious, driven, and execution-focused - Interested in building AI that is actually used in a business - Looking for an opportunity that can convert into a full-time role Preferred Qualifications: - Experience with LangChain, CrewAI, n8n, or similar frameworks - Knowledge of RAG, memory systems, and multi-agent architectures - Experience with system integrations or automation pipelines Required Skills: Python, AI agents, Large language models (LLMs), APIs, AI frameworks, LangChain, CrewAI, n8n, RAG, Memory systems, Multi-agent architectures, System integrations, Automation pipelines, Systems thinking, Independent work