---
title: "Discussion on \"A GenAI engineer's field guide for college students: RAG, fine-tuning, hackathons and shipping\" | Hashnode"
description: "Discussion on \"A GenAI engineer's field guide for college students: RAG, fine-tuning, hackathons and shipping\". Notes from mentoring 200+ students and building five production AI systems from Kanpur"
url: "https://hashnode.com/posts/pranjul-rathour-genai-engineer-campus-mentor-speaker/6a9c50049d1a9b586ff6e488"
---

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# [A GenAI engineer's field guide for college students: RAG, fine-tuning, hackathons and shipping](https://pranjulrathour.hashnode.dev/pranjul-rathour-genai-engineer-campus-mentor-speaker?utm_source=hashnode&utm_medium=feed)

Notes from mentoring 200+ students and building five production AI systems from Kanpur

Sep 5 · 9 min read · pranjulrathour.hashnode.dev  
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-   [#generative-ai](https://hashnode.com/tag/generative-ai)
-   [#rag](https://hashnode.com/tag/rag)
-   [#fine-tuning](https://hashnode.com/tag/fine-tuning)
-   [#hackathons](https://hashnode.com/tag/hackathons)
-   [#mentorship](https://hashnode.com/tag/mentorship)

## Written by

[PRANJUL RATHOUR](https://hashnode.com/@pranjulrathour)

@pranjulrathour · Bangalore, India

  
[View profile](https://hashnode.com/@pranjulrathour)

GenAI Engineer & AI Product Builder | Generative AI • LLMs • RAG • AI Agents • Fine-Tuning • QLoRA/LoRA • Multimodal AI • LLM Evaluation • C

GenAI engineer and AI product builder with 2+ years shipping production-grade AI systems — Retrieval-Augmented Generation (RAG) pipelines, fine-tuned LLMs, hybrid retrieval, and multi-modal AI applications spanning vision, speech, and OCR — architected end-to-end from data ingestion through deployment. Led engineering for a 14-member team building AI-powered products, pairing deep GenAI/ML engineering with full-stack delivery, while driving measurable business revenue as a startup technical lead.

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