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AI Automation Engineer with less than a year in LLM Development & AI Automation
Results-driven Generative AI Engineer and LLM Developer with a B.Tech in Artificial Intelligence & Data Science (2026). Experienced in designing and deploying production-grade AI systems leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), LangChain, Prompt Engineering, and OpenAI/Hugging Face APIs. Proven track record of building scalable AI automation workflows using n8n, FastAPI, and REST APIs that reduce manual effort by 70–80%. Passionate about solving real-world problems through intelligent AI agents, generative AI pipelines, and end-to-end LLM-powered applications. Seeking to contribute as a Generative AI Engineer at Polluxa, bringing hands-on expertise in AI model fine-tuning, vector databases, cloud deployment, and business process automation.
Poornima Institute of Engineering & Technology
B.Tech · Artificial Intelligence & Data Science
August 1, 2022 – June 30, 2026
MaxBrain Technologies
AI Automation Engineer Intern
December 1, 2025 – March 1, 2026
Jaipur, Rajasthan, India
AI-Based OCR to MCQ Generator
January 1, 2026 – February 1, 2026
Built an end-to-end OCR + LLM pipeline to convert PDFs and scanned images into structured MCQ datasets using Google Vision OCR and GPT-4, reducing manual content processing effort by 70%. Automated multi-step document-to-question workflow via n8n, cutting average processing time per document from 30 minutes to under 2 minutes.
Fine-Tuned LLM for Domain Adaptation (Tea Leaf Disease Expert)
December 1, 2025 – December 1, 2025
Fine-tuned GPT-4.1 Nano on curated tea leaf disease datasets, producing a domain-specific AI expert model with 90%+ response accuracy on plant disease queries. Applied advanced prompt engineering and supervised fine-tuning techniques to improve inference precision over a general-purpose baseline by 35%.
AI-Powered SEO Blog Automation System
November 1, 2025 – December 1, 2025
Developed a fully automated AI content pipeline for SEO blog generation, integrating topic research, AI writing, and direct WordPress publishing — reducing manual publishing time by 90%.
AI Educational Assistant for Competitive Exam Preparation
October 1, 2025 – November 1, 2025
Fine-tuned GPT-4.1 Mini on CBSE Class 10 Science chapter datasets, achieving 85%+ accuracy in generating subject-specific MCQs, explanations, and summaries. Implemented a RAG pipeline using LangChain and vector embeddings to enable context-aware question answering, reducing hallucination rate by 40%. Deployed the AI tutor as a FastAPI-based REST API endpoint, supporting 500+ concurrent student queries per session.
E-commerce Analytics Dashboard & Laptop Price Predictor
January 1, 2024 – December 31, 2024
Built a Laptop Price Prediction ML model using regression algorithms, achieving 92% prediction accuracy on a 1,300+ product dataset. Designed an E-commerce Analytics Dashboard in Power BI integrating SQL data pipelines to surface actionable business insights for sales performance tracking.
International Data Science & Machine Learning Program
GCI World
June 1, 2026 – Present
Artificial Intelligence, Prompt Engineering, Introduction to NLP, Introduction to Deep Learning, Data Science, Introduction to Automation Testing
Infosys Springboard
April 1, 2026 – Present
Cultural Fit Analysis
The candidate demonstrates a strong cultural fit for an AI Automation Engineer role, particularly in an innovative and fast-paced environment. Their portfolio showcases a passion for leveraging AI to solve real-world problems and automate complex workflows. The breadth of technologies used (LangChain, Hugging Face, n8n, FastAPI, various APIs, vector databases) indicates a continuous learning mindset and a willingness to explore diverse tools. The personal projects, alongside the internship, reflect initiative and a drive to build practical, impactful solutions, which aligns well with a product-focused or automation-centric company culture.
Soft Skills & Operational Fit
The candidate's project descriptions and internship experience highlight a proactive, results-driven approach to problem-solving. The focus on reducing manual effort by significant percentages (70-80%+) indicates a strong operational mindset geared towards efficiency and automation. The diversity of projects, from educational assistants to SEO automation and lead generation, suggests adaptability and a keen interest in applying AI to various business challenges. While direct collaboration experience is not explicitly detailed, the nature of building integrated systems implies an understanding of operational dependencies.