Skip to main content

Hi, my name is

Jay Patel

I build AI-powered platforms that ship.

Full Stack Developer who owns the entire lifecycle of enterprise AI platforms — from pixel to pipeline. Currently deep in the world of AI agents.

View Resume

01. About Me

I'm Jay — a Full Stack Developer building enterprise AI applications at scale. I work end-to-end: designing the interface, building the backend, integrating AI systems, and shipping the infrastructure that runs it all.

Right now I'm diving deeper into AI agents and what's possible at the frontier.

Technologies I've been working with recently:

languages:

TypeScriptPythonGolangJavaJavaScript

frameworks:

Next.jsReactNode.jsDjangoFlaskSpring Boot

cloud and_infra:

AWS (ECS, Bedrock, Lambda, S3)AzureTerraformDockerKubernetes

ai and_data:

AI AgentsStreaming APIsAmazon BedrockLLMsMongoDBPostgreSQLRedshift

devops:

JenkinsArgoCDPrometheusGrafanaGitHub Actions
Jay Patel

02.Education I've Pursued

Stevens Institute Of Technology

Candidate for Masters in Computer Science (MSCS) | Sep 2022 – May 2024 | Hoboken, NJ

GPA: 3.7

Courses: Cloud Computing, Agile Methods for Software Development, Artificial Intelligence, Data Analytics & Machine Learning, Database Management Systems

Gujarat Technological University

Bachelor in Computer Engineering | Jul 2017 – May 2021 | Anand, India

GPA: 8.39/10

Courses: Data Mining & Business Intelligence, Artificial Intelligence, Mobile communication and Networking, System Programming, Information & Network Security

03.Some Things I've Built

Technologies: Node.js, MongoDB, Handlebars, Docker, Kubernetes, Jenkins, Terraform, SonarQube, Prometheus

  • Full-stack web application for a solar energy company with dashboards for employees and customers, built with Node.js, Express.js, MongoDB, and Tailwind CSS.
  • Streamlines solar operations including task handling, customer support, sales, contract management, and crew task management.
  • CI/CD pipeline with Jenkins, SonarQube, Docker, and deployment to AWS EKS via ArgoCD.
  • Infrastructure as Code with Terraform; monitoring via Prometheus and Grafana.

Technologies: React, Django, Terraform

  • Full-stack app (Django + React) for automated AWS resource cleanup, optimizing infrastructure utilization and reducing costs.
  • Automated deletion of unused AMIs, EBS volumes, ECR repos, ECS/EKS clusters, IAM users, key pairs, RDS snapshots, and security groups via configurable retention policies.
  • Infrastructure drift detection by parsing Terraform state files against live AWS resources.
  • Intuitive React UI for resource selection, drift detection, and cleanup status.

Technologies: Python, Boto3, Terraform

  • CLI tool to detect drift between live AWS infrastructure (EC2, S3, RDS, IAM Roles, etc.) and Terraform state files.
  • Integrated Slack API for automated drift notifications to team channels.
  • Supports 'detect' mode (console output) and 'report' mode (Slack integration) with comprehensive drift reports.

Other Projects

Custom DNS Resolver

Golang

DNS resolver in Go with packet parsing, root server lookup, and iterative/recursive querying without external DNS dependencies.

Cloud Cost Optimization

Python, AWS Lambda, Boto3, CloudWatch

Reduced cloud expenses by 25% through automated Lambda-based resource cleanup across RDS, S3, EC2, and ECR.

AWS Glue ETL Pipeline

Python, AWS Glue, Terraform, Redshift

ETL pipeline using AWS Glue and Terraform to process 60,000+ property sales files into Redshift.

Credit Card Fraud Detection

Python, scikit-learn, Matplotlib

ML classification pipeline achieving 86% accuracy using Random Forest, Logistic Regression, KNN, and Decision Trees.

Data Warehousing with AWS Redshift

Python, SQL, AWS Redshift

ETL pipeline extracting 1M records from S3 into Redshift dimension and fact tables.

Automation of Code Maintenance

Ansible, Jenkins, AWS, Tomcat

CI/CD pipeline with Jenkins and Ansible playbooks for automated deployment to Tomcat on AWS.

pyFinance

Python, Pandas, Matplotlib

Python module for financial data analysis using Yahoo Finance and NSE APIs with candlestick charts, MACD, RSI, and moving averages.

Phishing URL Detection

Python, scikit-learn, XGBoost

ML pipeline for phishing URL classification using SVM, Random Forest, XGBoost, and Multilayer Perceptrons.

05.What's Next?

Get In Touch

If you like to say Hello to me, my inbox is always open. Whether you have a question or just want to say hi, I'll try my best to get back to you!