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Full Stack Engineer with less than a year in MERN Stack & Generative AI
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Passionate Full Stack Developer specializing in building intelligent applications that bridge the gap between traditional web architectures and Generative AI. Proficient in the MERN stack (MongoDB, Express, React, Node.js) with a strong focus on LLM orchestration using LangChain and RAG frameworks. I thrive in fast-paced environments and am eager to contribute to Pronix Inc.'s mission of automating enterprise workflows through conversational AI and agentic solutions. I am fully available for the 2:00 PM – 11:00 PM IST shift to support global collaboration.
Avanthi Institute Of Engineering and Technology, Hyderabad
B.Tech · CSE-Data Science
August 1, 2021 – June 30, 2025
SR JUNIOR COLLEGE
Intermediate
June 1, 2019 – May 31, 2021
TSMS
Secondary School
N/A – May 31, 2019
Manac Info Tech
Project Associative
January 1, 2025 – June 1, 2025
India
AI-Driven Business Process Automator
June 1, 2026 – Present
Created a custom Node.js API to orchestrate complex backend workflows and integrated it as a Custom Connector for Power Automate and Zapier. Designed an automated support ticket routing system that uses LLMs to categorize incoming queries and trigger specific business actions in a PostgreSQL database. Leveraged the Kore.ai XO Platform to build a virtual assistant capable of handling multi-turn dialogues for appointment scheduling and order tracking.
Enterprise Knowledge Assistant (RAG System)
June 1, 2026 – Present
Developed a full-stack Node.js/React application using LangChain and OpenAI to perform semantic search over unstructured PDF documents. Implemented a Retrieval-Augmented Generation (RAG) pipeline using Pinecone (Vector DB) to provide grounded, context-aware answers, reducing model hallucinations. Built a streaming chat interface in React that displays real-time AI responses and source citations for transparency.
Secure Application To Detect the Malicious URL Using Machine Learning
June 1, 2026 – Present
Developed a secure web-based application using machine learning models (Random Forest, SVM) to accurately classify URLs as malicious or benign, enhancing online threat detection. Implemented end-to-end pipeline including feature extraction from URLs, data preprocessing, model training, and real-time prediction, achieving over 90% detection accuracy.
Programming In Python
CIsco Network Academy
June 1, 2026 – Present
Mastering SQL
Intellipaat
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest in innovative areas like Generative AI and process automation, which suggests an alignment with forward-thinking and problem-solving cultures. The academic nature of projects and limited professional experience mean that direct evidence of cultural fit in a corporate setting is not yet available. The stated availability for a specific shift indicates a willingness to adapt to global team requirements.
Soft Skills & Operational Fit
The candidate's resume highlights collaboration, problem-solving, and logical reasoning skills through their internship description. The summary also indicates an eagerness to contribute and availability for a specific shift, suggesting good operational fit and a proactive attitude. However, without specific assessment data on communication, logical reasoning, or teamwork, a deeper evaluation of soft skills and operational fit is limited.