Junior Developer
Software Engineering
Sydney, NSW, Australia
Your Impact
Building & Shipping: Work alongside senior engineers to learn, build, test, and ship features across our React frontend and Node.js backend services. Pick up well-scoped tickets, ask great questions, and deliver clean, reviewed code into production.
Working with AI: Use AI coding assistants and LLM-based tools as part of your everyday workflow, applying them thoughtfully rather than blindly. Help integrate small AI capabilities (such as LLM calls, simple agents, or retrieval features) into product features and internal tooling under guidance from senior engineers.
Quality & Craft: Write tests, participate in code reviews (both giving and receiving feedback), and follow the team's engineering standards. Learn our codebase, our patterns, and our tooling, and contribute small improvements as you go.
Collaboration & Learning: Partner with product, design, and other engineers to understand the problem before writing code. Actively seek mentorship, share what you learn, and build relationships across the engineering team.
Operations Basics: Help triage bugs and support tickets, debug production issues with senior engineers, and contribute to documentation, runbooks, and observability for the features you ship.
About You
- 1-2 years of professional software development experience (internships, bootcamps, open source, or significant personal projects count)
- Working knowledge of at least one of JavaScript/TypeScript, Node.js, or Python
- Exposure to React or a similar modern frontend framework, and comfort with HTML and CSS
- Basic understanding of REST APIs, databases (SQL or NoSQL), and version control with Git
- Practical experience using AI tools in your work: AI coding assistants (such as Cursor, Copilot, Claude Code), prompt design, or basic LLM API integration (OpenAI, Anthropic, or similar)
- A computer science, software engineering, or related technical background, or equivalent self-taught experience
- Bonus: A side project, hackathon entry, or learning project that uses LLMs, RAG, or AI agents in a non-trivial way
- Bonus: Any exposure to cloud (AWS/GCP/Azure), CI/CD pipelines, or automated testing