AI-Augmented Software Engineer

- High level of proficiency in at least one programming language, with evidence you can learn new languages quickly - Experience writing and maintaining unit tests or other automated tests in any language or framework - Ability to take a feature or problem from idea through to production, including design, implementation, testing, and deployment - Strong interest in AI tools for software engineering, with a clear view on their strengths, weaknesses, and appropriate use - Comfortable reviewing and editing AI-generated code and content, rather than blindly accepting outputs - Good collaboration skills when working with cross-functional teams and stakeholders - Clear, concise written and verbal communication, including reporting on progress, trade-offs, and technical constraints - Demonstrated ability to balance delivery speed with code quality, security, and long-term maintainability - Habit of applying engineering best practices: version control, code review, documentation, and sensible testing - Experience using AI coding assistants (for example Claude Code, GitHub Copilot, or similar) in your day-to-day work (desirable) - Exposure to modern DevOps practices (CI/CD, infrastructure as code, monitoring, incident response) - Exposure to secure coding practices or application-level cyber security concerns - Experience working across different parts of the stack, or a track record of picking up new tools rapidly - A genuine interest in education and the impact of technology and AI on how people learn