Help & Supportcareers@gravityer.com
AI Engineer with less than a year in Python & LLM Integration
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
A Proactive Candidate (MCA-2025), actively seeking Entry-level AI/GenAI Development opportunities where I can apply my technical skills, learn from experienced professionals and contribute to impactful projects. Proficient in Python, LLM integration, LangChain, FastAPI, SQLite and Git version control. Proven ability to design, build, test and deploy End-to-end Software Applications on Cloud platforms.
SRM Arts and Science College
Master of Computer Applications (MCA)
August 1, 2023 – May 1, 2025
Kamban College of Arts and Science for Women
Bachelor of Computer Science
June 1, 2020 – May 1, 2023
CSC Computer Education Pvt Ltd.
Diploma in Computer Application · C,C++,HTML,CSS
August 1, 2019 – February 1, 2020
VEST-IN-VILLAGES
Data Analytics & QA
September 1, 2025 – March 1, 2026
India
CAMPERVAHN-IITM Incubated
Web Developer
December 1, 2024 – April 1, 2025
India
Facial Emotion Recognition System
June 25, 2026 – Present
Machine learning based real-time facial emotion recognition system using Python Libraries and ML algorithms. Implemented CNN-based algorithm for Facial emotion classification. Evaluated performance using accuracy and precision metrics. Built a real-time prediction interface using Python and OpenCV to capture webcam input and display the detected emotions.
RAG powered PDF QA Chatbot
June 25, 2026 – Present
Architected and deployed a full-stack Retrieval-Augmented Generation (RAG) chatbot capable of extracting, indexing and processing complex PDF documents to provide contextual, real-time question-answering capabilities. Engineered an asynchronous backend pipeline using FastAPI and Uvicorn, designing clean, high-performance RESTful API endpoints validated through interactive Swagger UI documentation. Built a robust document ingestion processor utilizing PyPDF and LangChain text-splitters to dynamically parse, segment and chunk unstructured textual data from large documents. Integrated Large Language Models (LLMs) by leveraging LangChain and Google Gemini API (text-embedding-004) to generate dense semantic embeddings from document chunks. Implemented vector similarity search using ChromaDB, allowing the system to accurately isolate and retrieve relevant source context with minimal latency to eliminate LLM hallucination. Configured secure cloud deployment on Render using GitHub-integrated automated CI/CD pipelines, optimizing dependency builds through explicit requirements.txt environment isolation and runtime environment variable masking.
View ProjectCultural Fit Analysis
The candidate's project diversity, including a personal RAG chatbot and an academic facial emotion recognition system, shows initiative and a strong interest in AI/ML. The internships, though not directly AI-focused, indicate a willingness to learn and contribute in different technical capacities (web development, data analytics, QA). The target role of AI Engineer aligns well with the candidate's stated career objective and recent project work, suggesting a good cultural fit for an innovation-driven environment.
Soft Skills & Operational Fit
The candidate demonstrates problem-solving, attention to detail, adaptability, and team collaboration skills through project descriptions and stated professional traits. The experience in an English-speaking team suggests good communication skills for operational fit. The ability to simplify complex tasks is a valuable trait for an AI Engineer role.