Architected and deployed a scalable, cloud-native blog infrastructure on Google Cloud, utilizing Cloud Run, Cloud Storage, and Cloud CDN for secure and efficient content delivery. Integrated BigQuery for advanced analytics and Cloud Logging for real-time monitoring. Leveraged Cloud Storage as a DataSink to optimize performance tracking and reporting. Additionally, implemented the Cloud Text-to-Speech API to convert articles into audio format, enhancing accessibility and user engagement. This solution ensures high availability, operational efficiency, and actionable, data-driven insights.

Developed and deployed a GraphRAG (Graph Retrieval-Augmented Generation) web application on Google Compute Engine, delivering highly accurate and contextually rich information about the Mission: Impossible film series. The application's backend, built with Flask and NetworkX, first constructs a detailed knowledge graph by using the Gemini LLM to extract entities and their relationships from source documents. For retrieval, it leverages semantic vector search (via cosine similarity) to identify relevant entities in the graph, then traverses their connections to build a comprehensive, structured context. This rich subgraph context is then passed to the generative model to produce nuanced and precise answers. For production, the application is served by a Gunicorn WSGI server, with Nginx configured as a high-performance reverse proxy. Communication between Nginx and Gunicorn is optimized through a Unix socket, ensuring a secure and efficient connection for real-time queries. The frontend is a static build from a React application, providing a sleek, responsive user interface.

Fine-tuned Google’s Gemma 2B model on a 4,000-sample subset of the Alpaca dataset using Low-Rank Adaptation (LoRA) to enhance instruction adherence and elevate response fidelity. Model performance was evaluated using perplexity scores, token-level accuracy analysis, and qualitative side-by-side comparisons, showcasing significant improvements in contextual understanding and output relevance.

Built a high-performance, security-hardened distributed log aggregation and analytics system on Google Cloud. A custom Virtual Private Cloud (VPC) with segmented web (x.y.1.0/24), app (x.y.2.0/24), and processor (x.y.3.0/24) subnets, each hosting a dedicated virtual machine (VM) and defined by specific CIDR blocks, ensures robust network isolation and adherence to zero-trust security principles. Firewall rules enforce strict access control, allowing only preconfigured IPs. A streamlined log ingestion pipeline securely transfers logs over SSH, processes data using Python, and integrates with Cloud Storage and Pub/Sub. Cloud Functions (1st gen.), triggered by Pub/Sub events, automate structured data ingestion into BigQuery. A Flask-based API provides controlled external access to processed logs and analytics

Designed an interactive platform to simplify technical concepts through dynamic visualizations. It offers interactive graphs and diagrams on topics like Python, Linux, Networking, Google Cloud, and AI. Built with React, Graphil serves as a powerful tool for learners and educators to understand complex topics through visual learning.

Created a detailed compliance guide for a fictional digital business, focusing on essential regulatory frameworks and cybersecurity standards. The guide provides actionable recommendations for areas like data protection, PCI compliance, risk management, and employee training, ensuring businesses align their operations with industry regulations to maintain a strong security posture.