Intern, Applied AI (2027)
About the role
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.
What you will learn:
- How enterprise generative AI solutions are identified, designed, built, tested, governed, deployed, and improved.
- How agents use trusted enterprise data, retrieval, APIs, citations, and controls to produce grounded responses.
- How to evaluate AI quality systematically and use evidence to improve prompts, knowledge sources, tools, and workflows.
- How multidisciplinary teams collaborate to deliver AI solutions in a secure, responsible, and scalable manner.
- How modern engineering practices, documentation, source control, and release processes support production AI delivery.
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;