MCP Engineer / AI Backend Engineer

About us

Ruby Labs is a leading tech company that creates and operates innovative consumer products. We offer a diverse range of opportunities across the health, education, and entertainment industries. Our innovative teams are driving the future of consumer-led products, and we're always looking for passionate individuals to join us. Learn more about our story at: https://rubylabs.com/about-us/

Overview

RubyLabs is expanding its AI and automation capabilities through MCP-based integrations, backend services, internal tools, and AI-powered workflows.

We are looking for an MCP Engineer / AI Backend Engineer who will design, build, and maintain MCP-based services and AI-powered backend systems. This role combines TypeScript, Node.js, Cloudflare Workers, backend engineering, AI tooling, and prompt engineering.

You will be responsible for developing production-ready MCP infrastructure, building backend services, integrating AI tools into internal workflows, and making AI-powered systems reliable, scalable, and easy to use.

About the Role

You will work on the development of MCP-based infrastructure and AI backend services used by internal teams and products.

You will work across:

MCP servers and clients

TypeScript / Node.js backend services

Cloudflare Workers

Backend frameworks such as Hono, Fastify, NestJS, or Next.js backend routes

AI workflows and prompt engineering

Internal automation systems

API integrations

Developer tooling

You will work closely with backend engineers, product managers, and internal stakeholders to build reliable AI-powered tools and backend systems.

What You’ll Do

MCP Development

Design, build, and maintain MCP servers and MCP-based integrations

Implement MCP tools, resources, prompts, and backend interfaces

Build reliable communication between AI agents, tools, and backend systems

Define clean contracts for MCP tools and services

Improve the stability, predictability, and maintainability of MCP infrastructure

Test MCP tool behavior across different usage scenarios

Monitor and improve the quality of AI-tool interactions

Backend Development

Build and maintain backend services using TypeScript and Node.js

Work with backend frameworks such as Hono, Fastify, NestJS, and Next.js backend/API routes

Implement REST APIs, internal endpoints, service-to-service integrations, and automation flows

Work with authentication, request validation, error handling, logging, and observability

Design clean, maintainable backend architecture for internal and production-facing systems

Write production-quality code with clear structure and good error handling

Cloudflare Workers

Build and deploy backend services on Cloudflare Workers

Work with edge runtime limitations and best practices

Design lightweight, performant services for edge/serverless environments

Debug issues related to worker execution, routing, request handling, and deployment

Use Cloudflare services when needed, such as KV, Durable Objects, Queues, R2, or D1

Optimize backend services for performance, reliability, and cost efficiency

AI & Prompt Engineering

Build AI-powered workflows and internal automation tools

Design prompts, system instructions, and tool definitions for reliable AI behavior

Improve the quality, consistency, and predictability of AI outputs

Analyze AI workflow failures and improve prompts, context, or tool contracts

Structure data and context for better LLM performance

Build testable AI workflows that can be evaluated and improved over time

Work with LLM APIs such as OpenAI, Anthropic, Claude, or similar providers

Integrations & Automation

Build integrations between internal systems, APIs, and AI tools

Automate repetitive operational or engineering workflows

Design backend flows that connect AI agents with real business systems

Ensure integrations are secure, observable, and maintainable

Build internal utilities and developer tools when needed

Debugging & Reliability

Investigate and fix issues across MCP servers, backend services, Cloudflare Workers, AI workflows, and API integrations

Improve logging, monitoring, and observability for AI/backend systems

Identify root causes of unreliable tool behavior or incorrect AI outputs

Make systems easier to debug, test, and maintain

Document technical decisions and implementation details clearly

About You

Must-Have

Strong experience with TypeScript

Strong experience with Node.js

Experience building backend services or APIs

Experience with at least one backend framework, such as Hono, Fastify, NestJS, or Next.js backend/API routes

Experience with Cloudflare Workers or similar serverless/edge environments

Good understanding of REST APIs, JSON, authentication flows, logging, and error handling

Experience building integrations between services and APIs

Interest in AI tools, LLMs, and automation

Experience with prompt engineering or AI workflow design

Ability to write clean, maintainable, production-quality code

Strong debugging skills

High ownership mindset and ability to work independently

Strong Plus

Experience with MCP / Model Context Protocol

Experience building MCP servers or MCP clients

Experience with OpenAI, Anthropic, Claude, or similar LLM APIs

Experience designing tool-based AI workflows

Experience with Cloudflare KV, Durable Objects, Queues, R2, or D1

Experience with PostgreSQL or other relational databases

Experience with internal developer platforms or automation tools

Experience with agentic workflows, function calling, or tool execution systems

Experience with payments, fintech, checkout flows, or orchestration platforms

Experience building production AI features, not only experimenting with prompts

How You Work

You are an engineer who enjoys building practical systems that solve real problems.

You can move between backend code, AI workflows, infrastructure, logs, and documentation. You understand that AI-powered systems need strong engineering foundations: clear interfaces, good observability, predictable behavior, and reliable error handling.

You are comfortable working with unclear requirements, turning them into working systems, and improving them through iteration.

You care about code quality, but you are also pragmatic and focused on delivering useful tools that people actually use.

You are comfortable working independently in a remote environment and taking ownership of technical decisions.

What We Offer

100% remote work

High trust and ownership

Direct impact on AI, automation, and internal engineering workflows

Opportunity to work with modern AI tooling and MCP-based infrastructure

Exposure to real-world backend systems and production workflows

Competitive compensation based on experience

Company-provided MacBook if needed

Unlimited PTO focused on outcomes, not hours

Life at RubyLabs

At RubyLabs, we value engineers who build reliable systems for real-world usage.

As an MCP Engineer / AI Backend Engineer, you will play a key role in developing MCP infrastructure, AI-powered backend services, and internal automation tools that help teams work faster and more effectively.

Equal Opportunity

Interview Process

After submitting your application, we conduct a thorough review which typically takes 3 to 5 days, but may occasionally take longer due to the volume of applications received. If we see a potential fit, we proceed with the following steps:

Recruiter Screening (40 minutes)

Technical Interview (90 minutes)

Final Interview (60 minutes)