AI Transformation / Forward Deployed Engineer (FDE) Internship

Datasite•Minneapolis, MN

1d•Onsite

About The Position

Datasite's Transformation Office leads enterprise AI adoption, operational transformation, and strategic change across the business. Our Forward Deployed Engineers (FDEs) partner directly with business teams to identify opportunities, rapidly prototype AI solutions, and help bring those solutions into production. As an AI Transformation / FDE Intern, you'll work alongside experienced FDEs on real business initiatives. You'll gain hands-on experience applying AI, automation, and modern engineering tools to solve operational challenges while learning how technology creates measurable business value. This internship is designed for someone with strong technical fundamentals, intellectual curiosity, and a builder's mindset. Enterprise experience isn't expected—we're looking for someone eager to learn, contribute, and grow.

Requirements

Recently completed a degree in Computer Science, Mathematics, Engineering or Data Science.
Experience with Python (strongly preferred) or another modern programming language.
Familiarity with APIs, SQL, databases, or workflow automation tools.
Strong analytical and problem-solving skills.

Nice To Haves

Experience with AI/ML, LLMs, or AI-powered development tools.
Academic, personal, or internship projects demonstrating automation or AI applications.
Experience with Git, cloud platforms, or workflow tools such as n8n.
Interest in business process improvement and enterprise AI.
Enjoy solving ambiguous problems.
Build things outside of class.
Ask thoughtful questions before jumping to solutions.
Learn new technologies quickly.
Communicate clearly with technical and non-technical audiences.
Take ownership and follow through.

Responsibilities

Learn the Discovery Process: Partner with FDEs during stakeholder meetings to understand business workflows, identify pain points, and learn how AI opportunities are identified and prioritized.
Build AI Solutions: Develop rapid prototypes using AI models, APIs, Python, workflow automation platforms, and other modern tools. Iterate quickly based on business feedback.
Explore Process Improvements: Analyze workflows across business functions to identify opportunities where AI and automation can improve productivity, quality, and customer experience.
Support Delivery: Help document use cases, participate in testing, prepare demonstrations, and support successful deployment of AI solutions.
Communicate Business Impact: Learn to explain technical work in business terms by focusing on measurable outcomes such as time savings, quality improvements, and efficiency gains.