Pratik Arjun Patil
Full Stack AI EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Full Stack AI Engineer with 1+ years in Python, React.js & Generative AI
Computer Science Engineering student with experience in Full-Stack Development, Artificial Intelligence, and Machine Learning. Skilled in Python, Java, React.js, FastAPI, JavaScript, SQL, LangChain, and REST API development, with hands-on experience building scalable web applications, AI-powered solutions, and RAG-based systems. Passionate about modern software engineering, Generative AI, and developing innovative solutions that solve real-world problems.
Walchand College of Engineering Sangli
Higher Secondary Certificate (HSC) · Maharashtra State Board
June 30, 2021 – May 31, 2022
K.N.P.V. Bhavaninagar, Sangli
Secondary School Certificate (SSC) · Maharashtra State Board
May 31, 2019 – May 31, 2020
D.Y. Patil Agriculture & Technical University, Kolhapur
Bachelor of Technology · Computer Science and Engineering
N/A – June 30, 2026
Star Softech
Internship - Software Engineer
May 31, 2025 – Present
Hubli, Karnataka, India
SmartHire Enterprise – AI-Powered Recruitment Platform
June 1, 2025 – June 1, 2026
Developed a production-ready AI-powered recruitment platform designed to streamline end-to-end hiring workflows for recruiters and candidates. Implemented AI-driven resume parsing and real-time ATS/Match Score generation to automate candidate evaluation against job requirements. Built interactive recruiter dashboards for candidate tracking, pipeline management, talent screening, and interview scheduling. Designed and integrated secure REST APIs using FastAPI with JWT authentication, password encryption, and role-based access control. Automated interview scheduling through secure 6-digit access passcodes, email notifications, and Google Meet link generation. Developed a responsive glassmorphic user interface using React.js, Vite, and Tailwind CSS with analytics dashboards and data visualizations. Ensured scalability, maintainability, and production-readiness through modular architecture and optimized frontend-backend integration. Technologies: React.js, Vite, Tailwind CSS, FastAPI, Python, MySQL, JWT, Bcrypt, REST APIs, Recharts, SMTP.
NovaQuest AI – RAG-Based Document Question Answering System
June 1, 2025 – June 1, 2026
Developed an AI-powered document question-answering platform using Retrieval-Augmented Generation (RAG) to generate accurate responses from uploaded documents. Built a responsive React.js interface for document upload, chat-based interactions, and natural language querying. Developed REST APIs using FastAPI for document processing, embedding generation, and user query handling. Integrated LangChain and OpenAI APIs to generate context-aware responses grounded in document content. Implemented ChromaDB vector database for efficient storage and retrieval of document embeddings. Enabled users to upload PDF documents and receive relevant answers through semantic search and retrieval pipelines. Designed a scalable RAG architecture combining document ingestion, vector search, and LLM-powered response generation. Technologies: React.js, Python, FastAPI, LangChain, OpenAI API, ChromaDB, RAG, PyPDF, Vector Embeddings.
GreenClassify: Vegetable Image Classification
June 1, 2025 – June 1, 2026
Developed a CNN-based deep learning model for automated vegetable image classification using TensorFlow and Python. Implemented image preprocessing, feature extraction, and model training pipelines to improve prediction accuracy. Enhanced model performance through hyperparameter tuning, data augmentation, and dataset optimization techniques. Applied computer vision and deep learning concepts for image recognition and classification tasks. Technologies: Python, Flask, TensorFlow, CNN, Deep Learning, Computer Vision, NumPy, Pillow, HTML, CSS, JavaScript
Restaurant Recommendation System
June 1, 2025 – June 1, 2026
Developed a content-based restaurant recommendation system using TF-IDF Vectorization and Cosine Similarity to suggest similar restaurants based on user preferences. Performed data cleaning, preprocessing, and feature engineering on a large-scale Zomato dataset using Pandas. Applied text processing techniques (Bag of Words + TF-IDF) on restaurant reviews and cuisines to improve recommendation accuracy. Built a Flask-based web application to serve real-time recommendations through an interactive user interface. Generated personalized recommendations by analyzing cuisines, ratings, cost, and customer reviews. Technologies: Python, Flask, Scikit-learn, Pandas, TF-IDF Vectorization, Cosine Similarity, HTML, CSS.
Personal Portfolio Website
June 1, 2025 – June 1, 2026
Developed a responsive personal portfolio website using React.js to showcase projects, skills, and achievements. Built reusable UI components and a modern interface using Tailwind CSS. Ensured full responsiveness and optimized user experience across desktop and mobile devices. Technologies: React.js, JavaScript, Tailwind CSS, Responsive Web Design
Cloud Practitioner Credit Course
Google for Developers (SmartBridge)
June 14, 2026 – Present
Data Science Credit Course
Google for Developers (SmartBridge)
May 10, 2026 – Present
Artificial Intelligence Credit Course
Google for Developers (SmartBridge)
March 29, 2026 – Present
Data Analytics Job Simulation
Quantium (Forage)
March 26, 2026 – Present
Cybersecurity Analyst Job Simulation
Tata (Forage)
March 22, 2026 – Present
Data Analytics Job Simulation
Deloitte (Forage)
March 1, 2026 – Present
Introduction to Generative AI
IBM
February 9, 2026 – Present
Cultural Fit Analysis
The candidate's diverse range of personal projects, particularly in AI and full-stack development, demonstrates a strong passion for technology and continuous learning, which aligns well with an innovative and growth-oriented culture. The focus on building practical, real-world solutions (e.g., recruitment platform, Q&A system) suggests a results-driven approach. However, the lack of team-based projects beyond the internship limits the assessment of collaboration in a larger organizational context.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and problem-solving mindset, essential for operational fit. The detailed breakdown of project contributions suggests good organizational skills and an ability to work independently on complex tasks. Collaboration skills are mentioned in the internship, indicating an understanding of team environments.