A Journey from Learner to GenAI Engineer
Karan Mehta rewrote his professional story with Uncodemy's GenAI track. Within a focused stretch of hands-on training, he built expertise in Python, LLMs, prompt engineering, and RAG — earning a 4.8 LPA offer as a GenAI Engineer at Iris Software, Gurugram.
Karan Mehta
GenAI Engineer
4.8 LPA
Salary Package
45
Days to Hire
Iris Software
Global Tech Solutions
Top 5%
Cohort Ranking
The Pivot
Before the Program
- No structured exposure to programming or AI tools.
- Confused about how to enter the generative AI industry.
- Weak grasp of LLMs, prompt engineering, and vector databases.
- Zero hands-on GenAI projects or GitHub presence.
After the Program
- Confident in Python, LLM APIs, LangChain, and RAG workflows.
- Built multiple end-to-end GenAI projects with clean documentation.
- Cleared every interview round with structured answers.
- Secured a full-time GenAI Engineer role at Iris Software.
The Learning Journey Timeline
Phase 1: Strengthening Fundamentals
Started with Python syntax, control flow, and core NLP concepts. Practiced data cleaning and exploratory analysis using Pandas and NumPy on real datasets.
Phase 2: Applied GenAI & LLMs
Moved into prompt engineering, LLM APIs, and Retrieval-Augmented Generation (RAG). Learned model fine-tuning, vector databases, and evaluation techniques through guided projects.
Phase 3: Interview Readiness
Focused on SQL query practice, GenAI case-study discussions, resume refinement, and live mock interviews to build confidence for real hiring rounds.
Core Tech Stack Mastered
Capstone Project Mastery
Intelligent Document Q&A System using RAG
GENERATIVE AIA Retrieval-Augmented Generation (RAG) system that allows users to upload documents and ask natural-language questions, receiving accurate, context-aware answers powered by LLMs.
Handling large, unstructured documents, reducing hallucinations, and maintaining context over multi-turn conversations while ensuring fast retrieval.
Built a complete RAG pipeline using LangChain, OpenAI embeddings, and Pinecone vector database. Implemented semantic search with chunking strategies and prompt engineering to generate reliable answers. Deployed via Streamlit for interactive use.
Performance Scorecard
Overcoming Challenges
Karan's biggest hurdle was moving from theoretical understanding to practical implementation of GenAI concepts. Topics like RAG, vector embeddings, and fine-tuning 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 models to interviewers.
Interview Preparation Intensive
Mock Interviews
Participated in 10+ mock sessions covering Python, SQL, LLM concepts, and GenAI system design 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, SQL, and basic GenAI questions within a strict time limit.
Technical Round
Answered live coding and concept-based questions on data wrangling, LLM APIs, and prompt engineering.
Case Study
Walked the panel through a complete GenAI 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
Iris Software
GenAI Engineer
Joining Iris Software in Gurugram as a GenAI Engineer, working with a leading global technology solutions provider to build data-driven AI products and insights.
Trajectory: The Ascent
Karan's compensation growth from his early roles to his current GenAI Engineer position at Iris Software, showing the steady climb that ended with a 4.8 LPA offer.
From Beginner to GenAI Engineer
- 1.5 LPA — Trainee / Intern
- 2.5 LPA — Junior AI Developer
- 3.5 LPA — AI Associate
- 4.0 LPA — AI Engineer
- 4.8 LPA — GenAI Engineer at Iris Software
Trainer & Mentor Team
"Karan had that rare mix of patience 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 GenAI 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 a GenAI Engineer at Iris Software. The structured curriculum, honest feedback, and relentless mentor support made all the difference."
- Karan Mehta
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