AI Engineer • Generative AI • Machine Learning Systems
AI Engineer specializing in building production-grade machine learning systems and LLM-powered automation platforms. Experienced in designing scalable data pipelines, optimizing predictive models, and deploying AI solutions across defense and enterprise environments.
I focus on transforming raw data into measurable business impact through intelligent system design.
- Reduced manual analytics and reporting effort by 70% via automated data pipelines (DRDO)
- Built LLM-powered AI agents with optimized prompt engineering and contextual memory handling
- Developed real-time ML regression systems for energy forecasting using temporal & weather-based signals
- Designed anomaly detection workflows for large-scale structured datasets
- Implemented CI/CD pipelines for automated AI deployment using GitHub Actions
- Delivered secure, cloud-deployed AI applications
Designed an end-to-end analytics and reporting automation system for .dat defense datasets.
- Built preprocessing pipelines for structured data ingestion
- Developed anomaly detection logic for operational insights
- Automated visualization and PowerPoint generation workflows
- Reduced manual reporting effort by 70%
Developed a real-time Energy Consumption Prediction System.
- Performed data cleaning, EDA, and feature engineering
- Built regression models using time-series and weather variables
- Improved model stability through iterative optimization
- Delivered deployable forecasting system prototype
Engineered LLM-based intelligent agents for automation and retrieval tasks.
- Built context-aware AI workflow agents
- Optimized prompt design for performance and reliability
- Integrated secure APIs for production use
- Implemented CI/CD automation pipelines
- Machine Learning (Regression, Optimization, Feature Engineering)
- Generative AI & LLM Agents
- Prompt Engineering & Context Architecture
- Model Evaluation & Performance Tuning
- Anomaly Detection & Predictive Analytics
- Python System Architecture
- Automation & Data Pipelines
- REST APIs (Flask)
- Data Visualization Systems
- Cloud Deployment & CI/CD
- Secure API Integration
Languages
Python • SQL • Java • C
Frameworks & Libraries
Scikit-learn • PyTorch • Flask • Streamlit • OpenCV
Cloud & DevOps
Oracle Cloud • AWS (Foundational) • GitHub Actions • Streamlit Cloud
- Oracle Cloud Infrastructure 2025 – Data Science Professional
- Oracle Cloud Infrastructure 2025 – Generative AI Professional
- NPTEL – Introduction to Machine Learning
- edX – Software Engineering Foundations
B.Tech — Computer Science Engineering
SR University
CGPA: 8.58