Intern, Applications Engineering (2027)

Position Summary

Join the App Engineering team as an App Engineering Intern and help build the modern, AI-enabled business applications that Hollister teams use every day. Working within our full stack engineering team, you will design, develop, test, and ship web and mobile applications, APIs, and integrations, using AI both inside the products you build and as a daily accelerator in how you build them. The role combines hands-on full stack development with AI-assisted engineering, user-centered design, and the engineering discipline required in a regulated medical device environment.

This internship is designed for talented undergraduate and master’s candidates who are eager to apply software engineering and AI skills to real business problems. Reporting to Saad Patel within the Digital Platforms & App Engineering function, the intern will work closely with full stack developers, integration engineers, AI engineers, architects, and business stakeholders while learning how an application moves from an idea and a prototype to a secure, supported, production release.

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 housingassistance for this opportunity.

Responsibilities

• Build Full Stack Applications: Design, develop, and test features across the front end, back end, and data layer of enterprise web and mobile applications, using technologies such as React, TypeScript, C#/.NET, Node.js, Python, REST APIs, and SQL.
• Engineer AI-Powered Features: Help embed generative AI capabilities into applications, including conversational interfaces, intelligent search, document and form understanding, summarization, recommendations, and agentic workflows, using Azure OpenAI, Azure AI Foundry, and related services.
• Accelerate Development with AI Tools: Use AI coding assistants and agentic development tools such as GitHub Copilot and Claude Code to scaffold, write, refactor, test, and document code. Learn to review AI-generated code critically for correctness, security, performance, and maintainability.
• Develop APIs and Integrations: Build and consume APIs and services that connect applications to enterprise systems such as SAP, data platforms, and SaaS applications, using Azure Functions, Azure API Management, Logic Apps, and custom connectors under the guidance of senior engineers.
• Prototype Rapidly: Turn business ideas into working proofs of concept in days rather than months. Evaluate emerging frameworks, low-code options such as Power Apps, and AI capabilities to recommend the right approach for feasibility, cost, and business value.
• Design for Users: Partner with stakeholders to understand workflows and pain points, translate requirements into user stories, and build intuitive, accessible, and responsive user interfaces. Gather feedback through demos and iterate quickly.
• Test and Ensure Quality: Write unit, integration, and end-to-end tests; support automated testing in CI/CD pipelines; and help evaluate AI features for accuracy, reliability, and appropriate behavior before release.
• Apply Secure and Responsible Engineering: Follow organizational standards for authentication, authorization, data privacy, secrets management, secure coding, and responsible AI. Never expose credentials or sensitive information, and keep appropriate human oversight in AI-driven features.
• Use Modern DevOps Practices: Work with GitHub or Azure DevOps for source control, branching, pull requests, code reviews, and automated build and deployment pipelines to Azure cloud environments.
• Collaborate Across Teams: Participate in agile ceremonies such as stand-ups, sprint planning, and retrospectives, and work with Data, Automation & Testing, AI, Infrastructure, and business teams, including global colleagues in India, Lithuania, and Mexico.
• Document and Present Results: Maintain clear technical documentation, architecture notes, and release notes. Present a working application or feature, along with lessons learned and recommendations, at the end of the internship.

Potential Project Exposure

• AI-enabled business applications that streamline manual processes for Supply Chain, Operations, Quality, Commercial, and Finance teams.
• Agentic AI applications that combine enterprise data, reasoning, and user-friendly interfaces to support faster, better-informed business decisions.
• Internal web and mobile apps with conversational or copilot-style experiences grounded in trusted enterprise data.
• API and integration services connecting applications to SAP and other enterprise platforms.
• Reusable application components, starter templates, and engineering standards for AI-assisted development.
• Low-code and pro-code solutions using the Microsoft Power Platform alongside custom-built applications.
• Automated testing, CI/CD pipelines, and observability for cloud-hosted applications.

Requirements

• Education: Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Software Engineering, Computer Engineering, Information Systems, Artificial Intelligence, or a related field. Candidate should remain enrolled in an academic program after the internship.
• Software Engineering Fundamentals: Solid understanding of programming concepts, data structures, object-oriented design, databases, and web application architecture through coursework or projects.
• Full Stack Programming Skills: Experience building applications with at least one front-end technology (e.g., JavaScript/TypeScript, React, Angular) and at least one back-end language (e.g., C#, Python, Java, Node.js). Comfortable writing SQL and working with REST APIs and JSON.
• AI Curiosity: Genuine interest in generative AI and large language models, both as features within applications and as tools that change how softwar