Engineering -AI Content Development – Summer Internship 2026
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About this role
Position Summary
The AI Content Development Intern will support the Engineering and PLM teams by applying generative AI tools to enhance the creation, organization, and usability of engineering training content. This role focuses on using AI responsibly to improve documentation workflows, support knowledge-sharing initiatives, and explore proof‑of‑concept capabilities such as an Engineering Knowledge Chatbot trained on SOPs, standards, PLM documents, and training materials.
This internship is ideal for students interested in AI, engineering systems, technical communication, and digital transformation in a real‑world industrial environment.
Key Responsibilities
- Use generative AI tools (e.g., Copilot, OpenAI platforms) to draft, summarize, refine, and restructure engineering training materials.
- Organize and convert source documents (SOPs, standards, PLM process instructions) into clear, structured training content.
- Assist in developing the foundation for an AI-powered engineering knowledge assistant, using curated engineering documents as training inputs.
- Validate AI-generated outputs for accuracy, clarity, and alignment with existing engineering processes.
- Work closely with Engineering, PLM, and Process Owners to ensure content correctness and update needed materials.
- Apply responsible AI practices, adhering to guidelines for confidentiality and internal data handling.
- Support continuous improvement initiatives related to engineering, knowledge management and training.
Learning Outcomes
By the end of the internship, the student will gain:
- Practical experience using AI responsibly within an engineering/PLM enterprise environment.
- Insight into engineering processes, PLM workflows, standards, and documentation practices.
- Exposure to real-world constraints on AI (accuracy limits, validation needs, governance).
- Hands-on practice improving training systems and knowledge-sharing capabilities.
- Professional development through mentorship, cross-functional collaboration, and structured project work.