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Ruby Labs

MCP Engineer / AI Backend Engineer

Reposted 12 Days Ago
Be an Early Applicant
Remote
Hiring Remotely in European Union
Mid level
Remote
Hiring Remotely in European Union
Mid level
The MCP Engineer / AI Backend Engineer will design, build, and maintain MCP-based services and AI-powered backend systems, utilizing TypeScript, Node.js, and Cloudflare Workers to develop reliable integration and automation tools for internal workflows.
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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

RubyLabs is an equal opportunity employer. All qualified applicants will receive consideration without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, age, or any other characteristic protected by law.

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)

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