My Projects

Enterprise AI/ML Platform

From Chaos to Control: Enterprise AI/ML Platform

Built a production-ready enterprise AI/ML platform on AWS solving real fintech challenges: automatic text summarization, real-time anomaly detection, comprehensive model management, and intelligent chatbot with 8 foundation models. Platform features ECS Fargate auto-scaling (2-20 tasks), Apache Airflow orchestration, AWS Bedrock integration, and intelligent caching achieving 60% cost reduction. Includes live monitoring dashboards, DevSecOps practices, and enterprise-grade security with IAM least privilege, S3 encryption, and GuardDuty threat detection.

AWS Bedrock ECS Fargate Apache Airflow MLOps Streamlit FastAPI CloudWatch DevSecOps S3 IAM

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Full-Stack Platform

Cloud-Native Job Portal Platform

Designed and built a production-ready job portal from scratch to solve real-world hiring inefficiencies. The platform features lightning-fast applications, organized admin dashboards, and zero-downtime reliability using AWS Lambda, RDS PostgreSQL, S3 static hosting, and API Gateway. Implemented environment-aware architecture handling different database schemas across dev/prod, JWT authentication, and secure file uploads with automatic cleanup.

AWS Lambda S3 RDS API Gateway PostgreSQL JavaScript DevOps

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Healthcare AI

AI Healthcare Patient Identity Verification

Built a production-grade serverless AI pipeline for Cleveland Medical Center to streamline patient check-in using facial recognition. The system registers patients with facial images at appointment scheduling and identifies them during check-in by matching faces against a secure collection using Amazon Rekognition, reducing identity mismatches and speeding up triage processes with strict healthcare data governance.

AWS Rekognition DynamoDB Lambda API Gateway Healthcare AI/ML Serverless

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Security Assessment

AWS Cloud Penetration Test: Real-World Risk Assessment

This penetration test evaluated the security posture of an AWS production-grade system across IAM, S3, TLS configurations, and compliance alignment. Findings included overly permissive IAM policies, public S3 buckets, and TLS misconfigurations. All findings were mapped to CIS Level 1 & 2 benchmarks using Prowler, with tooling support from Cloudsplaining, S3Scanner, SSLyze, and AWS CLI. The project demonstrates expertise in threat modeling, reconnaissance, audit automation, and practical remediation strategies for cloud-native architectures.

AWS IAM S3 TLS Prowler CIS Benchmarks Nmap AWS CLI

Redacted Report LinkedIn Article

Platform Engineering

FinBankOps: Secure, Multi-Region Kubernetes Infrastructure for Fintech

This project implements a production-grade, secure Kubernetes infrastructure for fintech using Amazon EKS. It supports multi-region deployment, blue/green releases, and GitOps-driven workflows via ArgoCD. Istio handles ingress traffic and internal service mesh routing, while security is reinforced using External Secrets Operator and kube-bench/kubescape audits. Observability is ensured via Prometheus, Grafana, and CloudWatch. The platform enables PCI-DSS-aligned compliance while providing scalable deployment for containerized microservices stored in Amazon ECR.

AWS EKS ArgoCD Istio Secrets Mgmt Prometheus Grafana KubeBench

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ML & DevOps

DevOps-Enabled Real-Time ML Fraud Detection System

This project showcases the complete pipeline for a real-time fraud detection system using a containerized microservices architecture on AWS. Ingestion, inference, and action microservices are deployed to Amazon ECS (Fargate), and their Docker images are stored in ECR. Machine learning inference is based on a trained model that detects anomalous financial transactions in real-time. Infrastructure is managed with Terraform, CI/CD is orchestrated via GitHub Actions, and observability is achieved through Amazon CloudWatch. Fraud alerts are published via Amazon SNS, and the architecture is extensible to support compliance audit logging using Amazon RDS.

AWS ECS Fargate GitHub Actions Amazon RDS SNS Terraform CloudWatch ML

Infra Repo App Repo LinkedIn Article

Application Platform

Secure Three-Tier Web Application on Kubernetes

This project focused on deploying a secure, scalable three-tier web application using AWS and Kubernetes. I provisioned a robust EKS cluster and built Docker containers for both frontend and backend services, hosted securely via AWS ECR. To route traffic efficiently, I configured an ALB Ingress Controller. For observability, I enabled CloudWatch control plane logs to track API server activities, authenticator logs, and audits. The infrastructure was designed to scale dynamically, with IAM roles enforcing principle of least privilege across services.

AWS Docker EKS Terraform CloudWatch IAM

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CI/CD & Infrastructure

Three-Tier Web App with GitHub Actions CI/CD

In this project, I built a fully automated, environment-aware deployment pipeline for a three-tier web application. The frontend was hosted on S3 while the backend (Node.js) ran on EC2 within a VPC. GitHub Actions orchestrated CI/CD pipelines across dev and prod branches. Infrastructure was provisioned with Terraform, including private/public subnets and NAT gateways. For monitoring, I installed the CloudWatch agent and configured AWS Managed Grafana dashboards with real-time CPU, memory, and disk usage metrics. Alerts were created for SLA-sensitive events. This setup exemplifies production-grade DevOps and cloud architecture.

AWS EC2 Terraform GitHub Actions S3 CloudWatch Managed Grafana

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Full-Stack Application

Cloud-Native Recipe-Sharing Application

To modernize the way I share culinary recipes, I developed and deployed a cloud-native FastAPI application integrated with a React frontend hosted on S3. The backend API was containerized and deployed to EC2, exposed via API Gateway. CloudFormation handled infrastructure provisioning. To ensure performance visibility, I configured Prometheus to scrape FastAPI metrics and visualized real-time traffic using Grafana dashboards. I designed two access layers: a user interface and an admin portal, reflecting real-world content management workflows.

AWS S3 React FastAPI EC2 CloudFormation Prometheus Grafana

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Full DevOps Pipeline

End-to-End DevOps Pipeline with EKS & ELK Stack

This project implemented a full-stack DevOps solution using GitHub Actions for CI, Terraform for infrastructure automation, and Kubernetes on AWS EKS for orchestration. Dockerized applications were built and deployed with Kubernetes manifests. Logs were centralized using the ELK stack, while Prometheus and Grafana enabled detailed performance monitoring and alerting. Security was reinforced through IAM policies, encrypted storage, and TLS via ACM certificates.

AWS Terraform GitHub Actions Docker EKS Prometheus Grafana ELK Stack

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Disaster Recovery

Automated Cloud Disaster Recovery Solution

This disaster recovery project leveraged AWS infrastructure to build a resilient architecture that could handle regional failover, backup, and restoration. Using Terraform for reproducible infrastructure and GitHub Actions for automation, I integrated Datadog for system observability and alerting to ensure readiness in business continuity scenarios.

AWS Terraform GitHub Actions EC2 S3 Route 53 Datadog

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Containerization

Containerized WebApp with CI/CD & Monitoring

This project involved containerizing a Node.js web app, deploying it using a CI/CD pipeline built with GitHub Actions, and configuring Prometheus and Grafana to provide visibility into app health and performance. The goal was to streamline releases and provide real-time monitoring of container behavior and HTTP requests.

Docker GitHub Actions Node.js Prometheus Grafana

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ML Deployment

ML Model Deployment with Flask on AWS

I deployed a Flask-based ML model as a production API on EC2 using Terraform and GitHub Actions. AWS CloudFormation and S3 were used for configuration and storage. Monitoring was integrated with Prometheus and Grafana, and AWS Security Hub was configured for compliance audits and vulnerability detection.

AWS Flask ML Model CloudFormation S3 EC2 Prometheus Grafana Security Hub

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Serverless CI/CD

Scalable Web App CI/CD with AWS Amplify

This project centered on building a CI/CD pipeline for a React-based web application. The frontend was deployed using AWS Amplify, and backend logic was handled with AWS Lambda. CodePipeline and CodeBuild automated deployments, and CloudWatch monitored performance metrics and logs.

AWS Amplify Terraform AWS Lambda RDS CodePipeline CloudWatch

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GCP Platform

Full-Stack Application CI/CD on Google Cloud

I deployed a full-stack application on GCP using Docker containers, Terraform for infra provisioning, and GitHub Actions for CI/CD. Monitoring and alerting were set up using the Google Cloud Operations Suite, providing clear visibility into deployments and runtime behavior.

GCP Docker Terraform GitHub Actions Cloud Run Monitoring

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Jenkins Pipeline

Node.js CI/CD with Jenkins & S3 Artifacts

This project focused on implementing an efficient Jenkins-based CI/CD pipeline for a Node.js application. Artifacts were managed and stored using S3. GitHub served as the version control system, and automated builds ensured fast feedback loops.

Node.js GitHub Jenkins Amazon S3

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Compliance Automation

AWS Infrastructure Compliance Audit System

This compliance audit system utilized AWS Config to evaluate resource conformance across services. Lambda functions were triggered on non-compliant rules, enabling proactive remediation and alerting via SNS.

AWS Config Lambda Compliance IAM

LinkedIn Article

Security Dashboard

AWS Cloud Security Dashboard

I designed a web-based dashboard to visualize and monitor key AWS security metrics, including IAM role usage, open security groups, and policy violations, offering centralized oversight for cloud posture management.

AWS IAM S3 Lambda CloudWatch

LinkedIn Article