A Journey from Learner to LLM Engineer
Raghav Shetty rewrote his professional story with Uncodemy's LLM track. Within a focused stretch of hands-on training, he built expertise in Python, large language models, prompt engineering, and fine-tuning — earning a 4.8 LPA offer as an LLM Engineer at Webfries, Gurugram.
Raghav Shetty
LLM Engineer
4.8 LPA
Salary Package
40
Days to Hire
Webfries
Digital Solutions
Top 10%
Cohort Ranking
The Pivot
Before the Program
- No structured exposure to programming or AI tools.
- Confused about how to enter the LLM engineering industry.
- Weak grasp of Python, transformers, and prompt engineering.
- Zero hands-on projects or GitHub presence.
After the Program
- Confident in Python, LLM APIs, and prompt engineering workflows.
- Built multiple end-to-end LLM projects with clean documentation.
- Cleared every interview round with structured answers.
- Secured a full-time LLM Engineer role at Webfries.
The Learning Journey Timeline
Phase 1: Strengthening Fundamentals
Started with Python syntax, control flow, and core AI concepts. Practiced data handling and model interaction using APIs and real datasets.
Phase 2: Applied Large Language Models
Moved into transformers, prompt engineering, fine-tuning, and RAG pipelines. Learned model evaluation, embedding techniques, and deployment through guided projects.
Phase 3: Interview Readiness
Focused on Python coding practice, case-study discussions, resume refinement, and live mock interviews to build confidence for real hiring rounds.
Core Tech Stack Mastered
Capstone Project Mastery
Domain-Specific LLM Chatbot
LARGE LANGUAGE MODELSA retrieval-augmented generation (RAG) project built to answer questions from large document sets, helping teams extract insights without manual reading.
Working with large, unstructured documents containing mixed formats and ensuring accurate, context-aware answers without hallucination.
Built a RAG pipeline using LangChain, vector embeddings, and an LLM API. Implemented semantic search, context injection, and response validation, then deployed via a Streamlit interface.
Performance Scorecard
Overcoming Challenges
Raghav's biggest hurdle was moving from theoretical understanding to practical implementation. Concepts like prompt engineering, embeddings, and RAG pipelines felt abstract until he started building projects from scratch. Regular mentor check-ins and daily coding practice helped him convert confusion into clarity, and by the final phase, he was confidently explaining his LLM models to interviewers.
Interview Preparation Intensive
Mock Interviews
Participated in 10+ mock sessions covering Python, LLM concepts, transformers, and prompt engineering with detailed feedback after each round.
Resume Workshops
Redesigned his resume around project outcomes and quantifiable results, making it ATS-friendly and recruiter-ready.
Soft Skills Training
Learned to frame answers using the STAR technique and to explain complex AI ideas in simple, business-friendly language.
Interview & Placement Process
Online Assessment
Solved a timed test with Python, AI fundamentals, and logical reasoning problems within a strict time limit.
Technical Round
Answered live coding and concept-based questions on LLMs, prompt engineering, and RAG pipelines.
Case Study
Walked the panel through a complete LLM project — from problem framing to deployment — with clear reasoning.
Managerial Round
Discussed teamwork, adaptability, and long-term career goals in an open conversation with the hiring manager.
The Offer
Webfries
LLM Engineer
Joining Webfries in Gurugram as an LLM Engineer, working with one of the world's leading digital solutions platforms to build AI-driven products and insights.
Trajectory: The Ascent
Raghav's compensation growth from his early roles to his current LLM Engineer position at Webfries, showing the steady climb that ended with a 4.8 LPA offer.
From Beginner to LLM Engineer
- 1.2 LPA — Trainee / Intern
- 2.0 LPA — Junior AI Associate
- 3.0 LPA — AI/ML Engineer
- 4.0 LPA — Senior AI Engineer
- 4.8 LPA — LLM Engineer at Webfries
Trainer & Mentor Team
"Raghav had that rare mix of curiosity and persistence. He never rushed through concepts — he sat with problems until they made sense. Watching him grow from writing his first Python script to confidently presenting a full LLM pipeline in interviews has been genuinely rewarding for our entire mentor team."
- Mentor Panel, Uncodemy
"I came in unsure whether I belonged in tech. I'm leaving as an LLM Engineer at Webfries. The structured curriculum, honest feedback, and relentless mentor support made all the difference."
- Raghav Shetty
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