Intern, Applied AI (2027)

Position Summary

Join the Data & AI team as an Applied AI Intern and contribute to real-world enterprise AI solutions. You will help design, build, test, and improve generative AI agents, knowledge assistants, retrieval solutions, and intelligent workflows that support business, R&D, Quality, and enterprise operations. The role combines hands-on solution development with applied research, evaluation, documentation, and responsible AI practices.

This internship is designed for talented undergraduate and master’s candidates who are eager to apply AI, software engineering, and analytical skills in a collaborative corporate environment. The intern will work closely with AI architects, engineers, IT specialists, and business stakeholders while learning how AI solutions move from business need and prototype to governed enterprise deployment.

Hollister Incorporated operates in a hybrid environment, Interns are required to come into the office in Libertyville Illinois a minimum of 4 days per week. Hollister does not provide relocation nor housing assistancefor this opportunity.

Responsibilities

• Contribute to AI Agent Development: Assist with the design, configuration, development, and testing of enterprise AI agents and copilots using Microsoft Copilot Studio, Azure AI technologies, Python, APIs, and related tools.
• Build Knowledge and Retrieval Solutions: Support retrieval-augmented generation (RAG), Knowledge Graph, enterprise search, document intelligence, semantic and vector search, metadata filtering, citations, and grounded response patterns across structured and unstructured information.
• Evaluate and Improve AI Quality: Create and execute evaluation scenarios; assess accuracy, relevance, grounding, citations, retrieval quality, response consistency, and usability; document defects and recommend improvements.
• Analyze Enterprise Content: Review SharePoint sites, documents, PDFs, spreadsheets, images, and other knowledge sources for AI readiness. Help identify OCR, content-quality, metadata, access, and indexing requirements.
• Prototype AI Solutions: Conduct focused research on emerging AI models, frameworks, APIs, orchestration approaches, and platform capabilities. Build small proof-of-concepts to assess technical feasibility and business value.
• Support API and System Integration: Help connect AI agents with enterprise services, custom connectors, APIs, Azure Functions, data platforms, and business applications under the guidance of senior team members.
• Apply Responsible AI and Security Practices: Follow organizational requirements for data protection, privacy, security, access control, human review, source grounding, and responsible use of AI. Avoid exposing credentials, sensitive information, or unsupported claims.
• Use Collaborative Development Practices: Work with GitHub, source control, branching, pull requests, documentation, and deployment pipelines to support collaboration, traceability, and recoverability of AI solutions.
• Collaborate Across Functions: Participate in requirements discussions, demonstrations, working sessions, and testing with IT, R&D, Quality, Data, Automation, and business teams.
• Document and Present Results: Maintain clear technical notes, solution documentation, test evidence, project updates, and implementation guidance. Present project outcomes and recommendations at the end of the internship.

Potential Project Exposure

• Enterprise knowledge agents and business-facing copilots, including Competitive Intelligence, Market Access, Finance, and R&D knowledge assistants.
• Quality Document Intelligence initiatives involving document search, comparison, metadata, product drawings, DHF/DMR analysis, traceability, and compliance-oriented workflows.
• Reusable AI-agent evaluation frameworks for regression testing, quality measurement, and release validation.
• Enterprise AI platform capabilities such as retrieval services, agent orchestration, knowledge graphs, context engineering, observability, governance, and reusable development standards.
• Digital Twin and simulation-related AI experiences, including data preparation, result analysis, workflow automation, and user interaction improvements.
• AI knowledge-source preparation, OCR assessment, SharePoint integration, GitHub collaboration, and CI/CD practices for AI solutions.

Requirements

• Education: Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Software Engineering, Information Systems, Engineering, or a related field. Candidate should remain enrolled in an academic program after the internship.
• AI and Software Fundamentals: Foundational understanding of artificial intelligence, machine learning, generative AI, large language models, software development, data structures, databases, or APIs through coursework or projects.
• Programming Skills: Experience with at least one programming language used for data or application development, preferably C# or Python. Ability to write understandable, maintainable code and troubleshoot technical issues.
• Communication Skills: Strong written and verbal communication skills, including the ability to explain technical concepts clearly to both technical and non-technical audiences.
• Collaboration and Learning: Curiosity, initiative, attention to detail, willingness to learn, and ability to work effectively with cross-functional teams in a fast-moving environment.

Preferred Skills (Bonus)

• Hands-on experience with generative AI, prompt engineering, AI agents, chatbots, RAG, embeddings, semantic search, or vector databases.
• Exposure Microsoft Copilot Studio, Microsoft Azure, Azure AI Search, Azure AI Foundry, Microsoft Fabric, Power Platform, or SharePoint.
• Experience using REST APIs, JSON, Git, GitHub, CI/CD pipelines, or cloud development environments.
• Familiarity with Python libr