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AI Engineer with 3+ years in AI systems, RAG, and Machine Learning
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Engineer with hands-on experience in building intelligent AI systems using LangGraph, MCP (Model Context Protocol) servers, and Retrieval-Augmented Generation (RAG) pipelines. Skilled in developing autonomous AI agents, designing FastAPI-based backend architectures, and implementing semantic search solutions using Pinecone vector databases. Strong foundation in machine learning, data analysis, and recommendation systems with prior industry experience in data analytics and automation testing. Seeking opportunities in Artificial Intelligence, Machine Learning, and Data Science to build scalable and impactful AI-driven applications.
M S Ramaiah Institute of Technology
B.E · Electronics and Communication Engineering
August 1, 2018 – June 30, 2022
Freelancer
Freelancer
November 1, 2025 – Present
India
Learnbay
Data Science Intern
December 1, 2024 – September 1, 2025
India
Alethea Communications Technologies Pvt Ltd
Software Engineer
October 1, 2022 – July 1, 2024
India
Power Consumption Analysis
June 29, 2026 – Present
Achieved optimal model performance (R2: 0.62) in predicting city power consumption using Random Forest and XGBoost regressors. Improved data quality by 40% through missing value imputation, type conversions, and IQR-based outlier treatment. Conducted in-depth exploratory data analysis and correlation analysis to uncover influential features like temperature and humidity. Deployed a multi-model comparison pipeline (Linear, Tree, Ensemble, SVM, XGBoost) to determine the best predictive strategy.
Term Deposit Subscription Predication
June 29, 2026 – Present
Developed a classification model using XGBoost and Random Forest to predict customer response to telemarketing campaigns with high AUC-ROC scores. Addressed class imbalance using SMOTE and improved overall prediction accuracy through scaling and hyperparameter tuning. Implemented end-to-end pipeline including label encoding, feature scaling, model training, and evaluation (precision, recall, F1-score). Visualized model performance using confusion matrix and ROC curve to enhance decision-making and model interpretability.
The candidate scored 94% on the 'Data Scientist — Artificial Intelligence' test, indicating a very strong grasp of the subject matter and related skills.
Strengths
Limitations
Cultural Fit Analysis
The candidate's project diversity, ranging from power consumption analysis to term deposit prediction and advanced AI agent development, demonstrates adaptability and a broad interest in applying AI/ML across different domains. The freelance experience in building an AI agent system aligns well with an innovative and self-driven culture. The previous roles as a Data Science Intern and Software Engineer, coupled with academic projects, show a progression towards AI/ML, indicating a focused career path. The breadth of skills listed, including various ML algorithms, RAG components, and backend development, suggests a versatile individual who can contribute to diverse technical challenges.
Soft Skills & Operational Fit
The candidate's resume highlights problem-solving, team collaboration, stakeholder coordination, and communication as soft skills. The project descriptions indicate an ability to work through complex technical challenges and collaborate on data-driven strategies. The psychometric test score (354/500) suggests a reasonable work attitude and stress handling, though not exceptionally high. The English test score (72/100) indicates adequate communication clarity for professional settings.