Results-driven AI and Machine Learning professional with hands-on experience designing, building, and deploying production-grade solutions. Specialized in orchestrating multi-agent systems and retrieval-augmented generation architectures, implementing core machine learning algorithms, and delivering measurable product and business outcomes. Proven expertise in translating stakeholder requirements into scalable architectures and operational workflows that drive organizational success.
Python • Java • C++ • JavaScript • MySQL
Oracle Cloud • AWS • Google Cloud Platform (GCP) • Microsoft Azure
Git • GitHub • Jupyter Notebook • FastAPI • PyTorch • LangChain • LangGraph • Agent Development Kit (ADK) • MCP • A2A
- AIF-C01: AWS Certified AI Practitioner
- AI-102: Microsoft Certified Azure AI Engineer Associate
- OCI-1Z0-1122-25: Oracle Certified AI Foundations Associate
- OCI-1Z0-1127-25: Oracle Certified Generative AI Professional
AI Engineer - Open Source Contributor
Google Summer of Code 2025, Eclipse Foundation | May 2025 – November 2025
- Architected and orchestrated a modular multi-agent system integrating specialized sub-agents with retrieval-augmented generation capabilities to maintain real-time repository context awareness, leveraging Model Context Protocol (MCP) server infrastructure for inter-agent coordination and asynchronous messaging
- Designed and implemented the REPD (Reconstruction Error Probability Distribution) algorithm utilizing autoencoder-decoder neural network architectures for probabilistic software defect prediction and anomaly detection in codebases, achieving statistically significant improvements through rigorous cross-validation and performance benchmarking
- Engineered comprehensive end-to-end data pipelines and GitHub Actions CI/CD workflows to automate data collection, preprocessing, cleaning, and feature extraction processes, enabling reproducible model training environments, continuous integration testing, and automated analysis reporting for production deployment