Backend & AI Automation Developer building APIs, data pipelines, n8n workflows, and LLM-integrated systems

n8n • APIs • Airtable • MongoDB • Node.js • Express • Ruby on Rails

Hands-on experience building backend systems, automation workflows, and structured data pipelines across Rails, MERN, and AI workflow projects.

Focused on backend architecture, API integrations, workflow automation, structured data validation, and AI-assisted classification systems.

Frontend: React, JavaScript, HTML, CSS Backend: Node.js, Express, Ruby on Rails Database: MongoDB, PostgreSQL API: REST APIs AI & Automation: n8n, Airtable, LLM workflows, prompt engineering Tools: Git, GitHub, Postman, Vite

Built full-stack systems using Ruby on Rails for real-world healthcare platforms:

• Designed MVC architecture and application structure

• Developed REST APIs and implemented full CRUD workflows

• Integrated PostgreSQL using ActiveRecord for data modeling

• Built admin dashboards for managing users, records, and workflows

• Implemented authentication and role-based access control

• Developed search, filtering, and pagination for large datasets

• Built structured forms and handled complex user input

• Implemented import/export functionality using CSV

• Built server-side logic for generating structured printable documents

• Contributed to frontend integration and resolved bugs in existing full-stack systems

• Worked primarily in development and testing environments, contributing to feature development, system improvements, and bug fixes in existing applications.

• Litigation Management System - legal workflow tracking and compliance
• Occupational Health Center - role-based workflows and structured data management

A backend workflow system designed to process unstructured partnership signals and convert them into structured, actionable data.

• Built an n8n workflow that starts from a brand website URL, discovers internal pages, filters low-value URLs, and classifies selected pages with LLMs
• Added structured output validation, normalization, fallback handling, and page-level sponsor-fit scoring
• Stored page-level evidence and aggregate brand assessments in MongoDB
• Sent review-ready company assessments to Airtable for prioritization and outreach review
• Added retry handling and staggered waits for more reliable LLM classification under provider rate limits

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A backend-first MERN application designed to demonstrate API design, authentication, validation, and scalable data workflows.

• Designed REST APIs with full CRUD functionality
• Implemented MongoDB with Mongoose for data persistence
• Built pagination, filtering, and search at database level
• Added protected authentication flows using JWT and bcrypt
• Integrated admin archive creation workflow with backend API and MongoDB persistence
• Structured the application into backend APIs, admin workflows, and user-facing archive views

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• Building n8n-based AI automation workflows with LLM classification, validation, and structured outputs
• Designing backend pipelines using APIs, MongoDB, Airtable, and workflow automation tools
• Improving workflow reliability through batching, retries, fallback handling, and rate-limit-aware execution

I started as a Ruby on Rails developer building full-stack client projects across frontend and backend systems, where I worked on CRUD workflows, admin dashboards, structured forms, API integrations, and production bug fixes.

Currently, I’m building Node.js, Express, React, and MongoDB applications with a backend-first approach while strengthening my frontend integration skills through hands-on project work.

I enjoy understanding how systems work end to end, from request flow and database operations to the UI behavior that depends on them.

• LinkedIn