Job Description – AI Engineer[Intern]
Position -Internship
Job Location -Mumbai
Qualification -B.Tech/M.tech/MCA [Pursuing or recently graduated]
Duration- 3-6 months
Stipend-30,000 per month
Role Overview
upGrad is building AI-native learning experiences for millions of working professionals globally. As an AI Engineering Intern, you will work directly on LLM-powered products — from prototyping intelligent solutions to improving overall learning experiences. This is a hands-on, builder role for someone who learns fast, ships faster, and is genuinely curious about what AI can do for education.
Job Description
AI/LLM development
- Build and experiment with LLM-powered features — including RAG pipelines, AI agents, and prompt engineering workflows — for upGrad's learning and content products.
- Develop and test prototypes for personalisation, content generation, and learner engagement use cases.
- Assist in evaluating model outputs for quality, relevance, and safety in an education context.
Collaboration & Integration
- Work closely with product managers, learning scientists, and senior engineers to translate learner problems into AI solution briefs.
- Integrate AI modules into existing product workflows using APIs and internal tooling.
- Document experiments, findings, and implementation decisions for cross-functional teams.
Research & Iteration
- Stay current with developments in LLMs, agentic frameworks, and AI in education; propose experiments worth running.
- Debug, test, and iterate model performance based on user feedback and product metrics.
Skills required
- Strong Python programming skills — you write clean, readable code, not just working code.
- Hands-on familiarity with LLMs, LangChain, RAG pipelines, or AI agents — through projects, coursework, or personal experimentation.
- Basic understanding of model evaluation and deployment concepts.
- Ability to work independently, ask the right questions, and communicate clearly with non-technical stakeholders.
- A builder's mindset — you default to let me try something before let me wait for a spec.
