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Generative AI Engineer with less than a year in LLMs & RAG
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Assessing your cultural and operational fit
Aspiring Generative AI Engineer with hands-on internship experience building production-grade LLM applications, RAG pipelines, and semantic search systems. Skilled in Python, LangChain, FAISS, Groq API, and HuggingFace Transformers, with proven expertise in vector embeddings and end-to-end GenAI development. Built real-world AI systems including a RAG-based Legal Assistant and PDF Q&A Chatbot. Actively seeking a full-time AI/ML or Generative AI engineering role.
Parul University
B.Tech · Computer Science & Engineering
August 1, 2020 – June 30, 2024
Rishabh Software
Artificial Intelligence & Generative AI Intern
January 1, 2026 – June 1, 2026
India
CXO Collaborate
Demand Generation Executive
April 1, 2025 – January 1, 2026
India
SVIQ Solutions Ltd
Web Development Intern
June 1, 2024 – March 1, 2025
India
AI Lawyer – GenAI RAG Legal Assistant
June 1, 2026 – Present
Built an AI-powered legal assistant using RAG architecture for legal Q&A and document analysis, integrating knowledge from FAQs, PDFs, and trusted legal websites with citation support. Implemented semantic search using Hugging Face embeddings and FAISS vector database; developed document upload, legal document summarization, and scenario-based legal guidance features.
View ProjectRAG-Based PDF Question Answering Chatbot
June 1, 2026 – Present
Built an end-to-end RAG pipeline that extracts, chunks, and embeds PDF content using LangChain and Hugging Face embeddings, storing vectors in a FAISS index for efficient semantic retrieval. Integrated Groq-hosted Llama 3.3-70B as the generative backbone, enabling context-aware, document-grounded responses with high accuracy on domain-specific queries. Deployed an interactive Streamlit interface allowing users to upload PDFs and receive precise answers in real time - demonstrating a production-ready GenAI application architecture.
LLM-Powered Generative AI Agents
June 1, 2026 – Present
Engineered a suite of 3 production-style GenAI applications an AI Cricket Commentary Generator, a Professional Email Drafting Agent, and a LinkedIn Post Generator - each powered by Groq-hosted Llama 3.3-70B via LangChain. Designed dynamic, multi-variable PromptTemplates with role-based persona injection (sports commentator, email agent, LinkedIn expert), demonstrating advanced prompt engineering techniques for diverse real-world use cases. Structured all tools with clean separation of concerns - environment variable management via dotenv, modular prompt design, and LLM invocation via LangChain's ChatGroq interface - reflecting production-ready coding practices.
View ProjectMovie Recommendation System
June 1, 2026 – Present
Built a content-based recommendation engine applying NLP preprocessing (tokenization, TF-IDF/cosine similarity) on Kaggle movie datasets to deliver personalized suggestions. Designed an intuitive Streamlit frontend allowing users to receive instant, ranked movie recommendations based on selected titles.
View ProjectCar Price Prediction System
June 1, 2026 – Present
Built a supervised ML model to predict used car prices, applying data preprocessing techniques including null-value handling, categorical encoding, and feature selection on a real-world dataset. Implemented and compared Linear Regression vs. Lasso Regression (L1 regularization), evaluating model performance using R² score to identify the better-generalizing model.
Veri5D - Engineering Consultants Website
June 1, 2026 – Present
Developed a react based web application for client specific needs. Added images and content as required. Enhanced the UI design. Made it responsive for mobile, tablet and laptop screens.
Internet of Things (IoT)
NPTEL
June 1, 2026 – Present
Fundamentals of Generative AI
AWS Skill builder
June 1, 2026 – Present
Building with the Claude API
ANTHROPIC Skilljar
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio shows a strong focus on Generative AI and Machine Learning, which aligns well with a Generative AI Engineer role. The diversity of projects (legal assistant, commentary generator, recommendation systems) indicates a broad interest and ability to apply AI in various domains. While the 'Demand Generation Executive' role is not directly technical, it suggests an ability to work in a fast-paced, metrics-driven environment and develop communication skills. The candidate's education and certifications further reinforce their commitment to AI/ML.
Soft Skills & Operational Fit
The candidate demonstrates analytical thinking through data analysis in their 'Demand Generation Executive' role and project work. Collaboration skills are mentioned in internship descriptions. The project descriptions show an ability to structure tools with clean separation of concerns, indicating good operational practices.