Generative AI Internship
Ship real LLM-powered features.
An 8–12 week paid internship where you build and deploy prompt pipelines, RAG systems, and LLM-backed features for real, client-adjacent product briefs, under a practicing AI engineer.
Move from LLM experiments to shipped AI features
This is the internship that follows our Generative AI training — you're placed on a real applied AI project, working on prompt design, retrieval pipelines, or fine-tuning problems that map to an actual product requirement.
You'll ramp up on the project's architecture and data in week one, move into guided pipeline work, and by the second half of the internship, you'll be owning a feature end to end, from design through evaluation and deployment.
What you'll work on
Real applied AI work, scoped to grow with your skill level.
Prompt & Pipeline Development
Design and refine prompts and pipelines for a real product feature.
RAG System Work
Build or extend retrieval-augmented generation components grounded in real data.
LLM API Integration
Integrate LLM APIs into an existing application with proper error handling.
Output Evaluation
Measure and improve output quality using evaluation and guardrail techniques.
Code Review Participation
Have your pull requests reviewed, and review others', as part of the team's workflow.
Deployment Support
Help take AI features through staging and into a deployed environment.
Technologies you'll work with
How the internship is structured
A four-phase structure that moves you from onboarding to owning a real AI feature.
01. Onboarding & Project Ramp-up
Week 1- Tooling and environment setup
- Project architecture and data walkthrough
- Meet your mentor and team
- First small, guided task
02. Guided Pipeline Work
Weeks 2–6- Paired work on real prompt and RAG tickets
- Daily standups and sprint planning
- Code review on every pull request
- Mid-internship progress check-in
03. Independent Feature Ownership
Weeks 7–10- Own a feature end-to-end with mentor support
- Run evaluation and guardrail checks
- Participate in deployment
- Document your work for the team
04. Final Presentation & Evaluation
Weeks 11–12- Present your shipped work to the team
- Mentor evaluation and written feedback
- Certificate and LOR eligibility review
- Full-time opportunity discussion, if applicable
The kind of work interns actually ship
Real examples of feature scope Generative AI interns take on.
Internal Documentation Assistant
Built a RAG-based Q&A feature over internal documentation for an active engagement.
Prompt Pipeline Optimization
Improved reliability and cost of an existing content-generation prompt pipeline.
Support Summarization Feature
Shipped a feature that summarizes and tags incoming support tickets automatically.
What makes this internship real
Real Product Briefs, Not Sandboxes
You work on AI features tied to actual product requirements, not isolated notebooks.
A Named Mentor
You're paired with one AI engineer for the full internship who reviews your work and tracks your growth.
Iterative, Evaluation-driven Workflow
You practice the test-and-refine loop real AI teams use to improve output quality.
Eligibility
Basic Python Knowledge
Comfortable reading and writing basic Python is expected.
LLM Exposure Helpful
Prior exposure to LLM APIs or our Generative AI training program is a plus, but not mandatory.
Full-time Availability
Able to commit to a full-time, weekday schedule for the internship's duration.
A GitHub Profile
Any prior project work or coursework repos you can share with your application.
What you walk away with
Performance-based Stipend
A paid internship, with stipend tied to your track and prior experience.
Certificate of Completion
Awarded to every intern who completes the program's full evaluation.
Letter of Recommendation
Issued to strong performers based on their mentor's written evaluation.
A Real Shipped Portfolio
A deployed AI feature you can show and speak to in interviews.
Full-time Consideration
Top performers are considered first when Generative AI Engineer roles open.
A Direct Mentor Reference
A working AI engineer who can speak to your work firsthand.
Why intern with YashOrbit
You Ship, Not Just Learn
Every intern's work goes into a real deployed AI feature, not a personal sandbox project.
Mentors Who Are Still Building
You're reviewed by engineers actively shipping generative AI features to clients.
A Clear Path to Full-time
Strong performance is the primary path to a full-time offer, evaluated transparently.
Frequently asked questions
Yes, this is a paid internship with a performance-based stipend, shared with you during the selection process.
Ready to intern on real Generative AI work?
Apply for the Generative AI internship and start shipping LLM-powered features that actually go live.