Develop and test Gen AI features, moving from proof-of-concept to real-world deployment.
Design RAG pipelines and conduct prompt engineering experiments to make LLMs smarter and more accurate.
Translate human needs into technical user stories. You are the bridge between a client’s "I wish" and a developer’s "I built."
Evaluate AI outputs for accuracy, bias, and safety. You are the guardian of responsible AI.
Participate in code reviews, pair programming, and sprint planning like a full-time engineer.

Requirements

You’re currently enrolled in an Undergrad or Grad program in Computer Science or relevant field (graduating in 2026 or 2027).
You speak Java or JavaScript and have a solid grasp of LLMs, Co-pilot concepts, and Retrieval-Augmented Generation (RAG).
You’re proficient with Git/ GitHub and common developer tools.
You enjoy creating and building. (We’d love to see your GitHub or a project portfolio!)
You can explain a complex "why" to a non-technical audience.
Exposure to cloud platforms like AWS/Azure/GCP is preferred.

Benefits

Direct Mentorship: Learn from the visionaries who are literally shaping the future of enterprise tech.
Senior Access: Direct visibility with leaders who want to hear your ideas.
Real Curriculum: A structured training program designed to help you gain experience working on impactful real-world project.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

JavaJavaScriptLLMsCo-pilot conceptsRetrieval-Augmented Generation (RAG)prompt engineeringcode reviewspair programmingsprint planningGit

Soft Skills

communicationtranslating technical conceptsevaluating AI outputsresponsible AI advocacycollaborationproblem-solvingcreativityexplanation skills