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AI Engineer with less than a year in Python & LangChain
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
B.Tech graduate in Artificial Intelligence and Machine Learning with hands-on experience in Generative AI, Python development, LLM applications, and API integration. Experienced in building Retrieval-Augmented Generation (RAG) systems and AI-powered applications using LangChain, LangGraph, FastAPI, and LLM APIs. Strong problem-solving skills with a passion for building practical AI solutions.
Vignan's Institute of Engineering for Women
B.Tech · Artificial Intelligence & Machine Learning
August 1, 2022 – June 30, 2026
Labmentix Pvt. Ltd.
AI/ML Intern
October 1, 2025 – April 1, 2026
India
Mirai School of Technology
AI Summer Intern
July 1, 2025 – August 1, 2025
India
AI Code Review Agent
June 24, 2026 – Present
Developed an AI-powered code review assistant using Python and LLM APIs. Automated code analysis and feedback generation workflows. Applied prompt engineering techniques to improve response quality.
Multi-Document RAG Question Answering System
June 24, 2026 – Present
Built an AI-powered document question-answering application using Python, FastAPI, LangChain, and LLM APIs. Implemented document ingestion, retrieval, and response generation workflows. Improved answer relevance using retrieval-augmented generation techniques.
IBM Python for Data Science, AI & Development
IBM
June 1, 2026 – Present
The candidate scored 50% on the Python Internship Test, indicating a basic understanding of Python fundamentals but significant gaps in advanced topics, algorithms, unit testing, and data streaming.
Strengths
Limitations
Cultural Fit Analysis
The candidate's project diversity, focusing on AI Code Review and RAG systems, shows a clear interest and alignment with modern AI development. The internship experiences, though short, indicate a proactive approach to gaining practical exposure. The skills listed on the resume align well with the target role, suggesting a good cultural fit for an AI-focused team.
Soft Skills & Operational Fit
The psychometric test score of 304/500 suggests average performance in logical reasoning, work attitude, stress handling, and team collaboration. The English test score of 82/100 indicates good communication clarity and professional language usage. The candidate's project descriptions are clear and concise, reflecting good written communication.