Remote Ruby Engineer for AI-Driven Backend APIs

Alignerr Corp.; España; Remote; EUR 41,000 - 83,000; Part time

Benefits offered by this job

Fully remote

Flexible hours

Job summary

Alignerr is seeking an experienced Ruby Software Engineer to design, evaluate, and improve real-world software systems used in AI training and data-driven workflows. This is a fully remote, hourly contract role designed for working engineers who want flexible hours and meaningful, high-impact work.

You will develop backend services, review code for performance and maintainability, and collaborate asynchronously with researchers and engineers to support AI training and evaluation efforts.

Qualifications

• 2+ years of professional software engineering experience.
• Strong proficiency in Ruby and backend development concepts.
• Comfortable with production codebases, RESTful APIs, and data-driven systems.
• Self-motivated and able to work independently without close supervision.

Responsibilities

• Develop and maintain backend services and APIs using Ruby and Ruby-based frameworks.
• Review, analyze, and improve existing codebases for correctness, performance, and maintainability.
• Evaluate realistic software engineering scenarios to help create and validate high-quality technical datasets.
• Collaborate asynchronously with researchers and engineers to support AI training and evaluation efforts.
• Apply production-grade engineering thinking to real-world backend and API problems.

Skills

Ruby

Backend development

RESTful APIs

Analytical thinking

Independent work

Code quality

Tools

Ruby on Rails

Testing frameworks

Performance profiling

AI tooling familiarity

Job description

Alignerr is seeking an experienced Ruby Software Engineer to design, evaluate, and improve real-world software systems used in AI training and data-driven workflows. This is a fully remote, hourly contract role designed for working engineers who want flexible hours and meaningful, high-impact work.

You will develop backend services, review code for performance and maintainability, and collaborate asynchronously with researchers and engineers to support AI training and evaluation efforts.