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AI Engineer with less than a year in MERN stack, Python, and Machine Learning.
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Aspiring Full-Stack Developer and AI enthusiast with strong foundations in MERN stack development, data analysis using Python, and AI/ML application development. Skilled in building scalable web applications, RESTful APIs, and AI-powered solutions including RAG-based chatbots and Text-to-SQL systems. Seeking an entry-level role to apply software engineering and AI skills to real-world products.
Malla Reddy University
B.Tech · Computer Science Engineering
August 1, 2022 – June 30, 2026
Sri Sai Saraswathi Vidyanikethan
SSC (Class X)
June 1, 2020 – May 31, 2020
Sri Chaitanya Junior College
Intermediate (Class XII)
June 1, 2020 – May 31, 2022
Text-to-SQL AI System
June 1, 2026 – Present
Developed a natural language to SQL query generation system using a Large Language Model (LLM) and prompt engineering. Enabled non-technical users to query databases by typing plain English questions, which are automatically converted to valid SQL. Built schema-aware prompting so the model understands table structures, column names, and relationships before generating queries. Validated generated SQL queries by executing them against a live database and returning results to the user in a readable format. Achieved accurate query generation across SELECT, JOIN, GROUP BY, and aggregation operations on multiple datasets.
RAG-Based AI Chatbot
June 1, 2026 – Present
Built a Retrieval-Augmented Generation (RAG) chatbot that answers user queries from custom documents using LangChain and OpenAI API. Implemented document ingestion pipeline to chunk, embed, and store data in a FAISS vector database for semantic search. Designed a conversational interface that retrieves the most relevant context chunks and generates accurate, grounded responses. Integrated memory to maintain multi-turn conversation history for a coherent chat experience. Reduced hallucination by grounding model responses strictly on retrieved document context.
Amazona - Scalable E-commerce Platform
June 1, 2026 – Present
Developed a full-stack e-commerce application using React, Node.js, and MongoDB. Integrated Razorpay payment gateway for secure online transactions and order processing. Designed an admin dashboard with analytics for users, orders, and revenue visualization. Built RESTful APIs with optimized queries and pagination to improve performance and scalability. Added product search, filtering, and review system to enhance user experience. Deployed front-end and server components using Vercel and Render, and hosted data on MongoDB Atlas.
Global Groundwater Depletion Analysis
June 1, 2026 – Present
Processed and analysed multi-decadal groundwater datasets using Python, Pandas, and NumPy to surface regional depletion trends. Cleaned and transformed 100+ records across many countries. Produced visualisations and a summary report identifying critical depletion trends in key regions.
Solutions Architecture Virtual Experience
Amazon Web Services (Forage)
June 1, 2026 – Present
Data Analytics Virtual Experience
Deloitte (Forage)
June 1, 2026 – Present
Python Data Representation
University of Michigan (Coursera)
June 1, 2026 – Present
Software Engineering Virtual Experience
Accenture (Forage)
June 1, 2026 – Present
Internet of Things
NPTEL (IIT)
June 1, 2026 – Present
Programming Essentials in Python
Rice University (Coursera)
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio shows a diverse interest in both AI/ML and full-stack development, suggesting adaptability and a willingness to explore different technical domains. The personal projects are well-described and demonstrate initiative. The target role of 'AI Engineer' aligns well with the recent AI-focused projects. The breadth of skills, from web development to data analysis and AI, indicates a curious and learning-oriented individual, which generally contributes positively to cultural fit in dynamic tech environments.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving mindset and an ability to translate complex requirements into functional solutions. The focus on reducing hallucination in chatbots and ensuring accurate SQL generation demonstrates attention to detail and a commitment to quality. However, without direct work experience, it's difficult to assess stress handling, team collaboration, or adaptability in a professional operational environment.