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AI Engineer with less than a year in deep learning, machine learning, and multi-agent systems.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Highly motivated and results-driven AI Engineer with a strong foundation in Python, deep learning, and machine learning. Proven ability to design, build, and deploy intelligent applications using modern AI frameworks like LangChain and Streamlit. Experienced in developing end-to-end ML workflows and crafting multi-agent systems for complex problem-solving. Eager to contribute expertise in AI development to innovative projects.
Invertis University
Bachelor of Computer Applications
August 1, 2024 – Present
Greenwood Senior Secondary School
Intermediate · PCB
April 1, 2020 – May 1, 2022
Greenwood Senior Secondary School
Matriculation · Science
March 1, 2018 – May 1, 2020
App Builder – AI-Powered Coding Assistant
December 1, 2025 – Present
Built an AI coding assistant (App Builder) that generates complete projects from natural language requests. Designed a multi-agent system with Planner, Architect, and Coder Agents for task decomposition and code generation. Enabled creation of full-stack apps, APIs, and scripts autonomously using LangGraph and Groq API.
Stock Price Prediction
November 1, 2025 – Present
Built an LSTM-based model to predict stock closing prices using historical market data. Developed a Streamlit web app for interactive visualization and user-driven predictions. Deployed the application using GitHub and Streamlit Cloud for real-time inference.
Machine Learning with Python
Coursera
January 1, 2026 – Present
5-Day AI Agents Intensive Course with Google
Kaggle
November 1, 2025 – Present
100 Days of Code™: The Complete Python Pro Bootcamp
Udemy
November 1, 2025 – Present
Introduction to Deep Learning & Neural Networks with Keras
Coursera
November 1, 2025 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest in cutting-edge AI technologies (AI agents, LLMs) and a proactive approach to learning through certifications and personal projects. The diversity of projects (AI coding assistant, stock prediction) shows a broad interest in applying AI to different domains. The competitive programming background suggests a drive for problem-solving and continuous improvement, which can be a good cultural fit for an innovative and challenging environment. However, the lack of team-based projects or professional experience limits the assessment of collaboration and interpersonal cultural fit.
Soft Skills & Operational Fit
The candidate lists communication, teamwork, adaptability, analytical thinking, and being a learner as soft skills. The project descriptions are clear and concise, indicating good written communication. The focus on building complete applications and deploying them suggests a practical, results-oriented approach. However, without direct work experience or psychometric test results, it's difficult to fully assess operational fit and how these soft skills translate into a team environment.