SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Imagine Learning UK (formerly Twig Education, acquired by Imagine Learning in 2021) is seeking a Senior Software Engineer to join one of their Ruby on Rails teams. The company provides comprehensive multimedia learning experiences for students across science, mathematics, English language, arts, and other disciplines.
In this role, you will solve real problems and ship secure, well-tested features built to last. You'll be fluent in Rails conventions and comfortable taking ownership of system components end-to-end, from data model through deployment. AI-assisted development is embedded in the workflow here—you'll use agentic coding tools like Claude Code or GitHub Copilot as part of daily development, applying judgment on when they help and when a more considered approach is needed.
Key responsibilities include:
- Analyzing requirements with Product Owners and translating them into practical solution designs with realistic timelines
- Writing Ruby on Rails code following established team conventions, prioritizing clarity, maintainability, and long-term quality
- Using AI coding assistants as a normal part of development while reviewing and validating generated code with rigor
- Contributing to development and maintenance of the team's AI tools to ensure coding agents produce output aligned with team standards
- Writing RSpec tests to provide confidence in application behaviors and identify unintended impacts before production
- Using metrics and observability data to identify improvement opportunities and strengthen logging
- Working confidently with PostgreSQL, MySQL, and similar databases (schema design, migrations, query performance)
- Participating in on-call rotation to respond to customer-impacting issues
- Taking ownership of packaging and releasing work through CI/CD pipelines
- Contributing to pull request reviews to maintain code quality
- Creating clear documentation capturing technical decision reasoning
- Supporting and mentoring other engineers in Ruby, Rails, and responsible AI development tool use
- Proactively identifying areas for application improvement and working with Product Owners on prioritization
The office is located in Glasgow's West End near parks, cafes, and restaurants, with friendly office dogs. Flexible hybrid working options are available.
QUALIFICATIONS:
- Bachelor's or master's degree in Computer Science, Software Engineering, or related field (desirable but not essential)
- 5+ years of professional software engineering experience, including at least 3 years working in Ruby on Rails
- Strong command of Ruby on Rails, including ActiveRecord, service objects, and background jobs (Sidekiq or similar)
- Comfortable designing and testing Rails applications using RSpec and FactoryBot or equivalent testing stack
- Able to work independently on business problems using sound judgment and seeking guidance when needed
- Good understanding of AWS and how services are deployed and scaled
- Practical, hands-on experience with AI coding assistants, understanding how to prompt effectively and review generated output critically
- Comfortable reviewing AI-generated code and pull requests with same care as human-authored code, considering security, performance, and Rails best practice
- Working knowledge of Docker and CI/CD pipelines (GitHub Actions, Jenkins, or similar)
- Proactive approach to quality, including adding appropriate tests, logging, and observability
- Able to create clear, concise documentation
- Some experience with JavaScript, Python, or Terraform useful but not required
- Able to support and mentor other Software Engineers, including junior team members
- Builds trust and influences others using facts, evidence, and thoughtful reasoning
- Communicates effectively with Product Owners, engineers, and stakeholders at different levels
- Approaches disagreement and challenging conversations calmly and constructively
- Champions team best practices in testing, documentation, and AI coding conventions
- Comfortable working with ambiguity and adapting as AI tooling and development practices evolve
