ContextJet AI is a fast-growing AI startup delivering NLP solutions for a global client network. This article outlines a continuous, remote internship opportunity for college students in their 2nd through final year, the practical learning benefits, the technical skills and experience sought, and the internship format and preferred candidates.
About ContextJet AI and perks
ContextJet AI builds real-world AI projects and delivers NLP solutions for clients across multiple countries. Interns will gain hands-on experience and highly in-demand skills by contributing to the development of multiple complex, real-world AI projects.
- Client locations include USA, Canada, Dubai, Mexico and India.
- Experience gained is practical and project-focused, across several client engagements.
Skills and experience we seek
We are looking for students who can learn and develop quickly, with concrete AI experience and strong debugging ability in backend pipelines. Key skills and technologies explicitly valued:
- Speed: ability to think, learn and develop fast with little hesitation and confidence in execution.
- AI experience: AI agents (LangGraph/n8n), LangChain, RAG, Knowledge Graphs.
- Fast prototyping and vibe coding: tools such as Cursor, Claude Code, Codex, Windsurf.
- Debugging: strong debugging skills in AI backend pipelines.
- Bonus: Web-application development experience, AWS experience (EC2 and Bedrock), and system design knowledge.
Internship format and preferred candidates
The internship is remote and runs on a continuous rolling basis during college terms rather than tied to a specific summer or winter period. It is intended for students in their 2nd year through final year who are eager to learn, build, and grow.
Summary: ContextJet AI offers a remote, continuous internship where students can build real-world AI and NLP experience for international clients. Candidates should be fast learners with AI agent, LangChain, RAG, and knowledge graph experience, rapid prototyping skills, and strong backend debugging; web, AWS, and system design experience are bonuses. The opportunity is aimed at 2nd year to final year college students.
