The company is your AI transformation partner. Founded in 2016 and headquartered in Melbourne, they have AI-augmented engineering teams in both Australia and Ho Chi Minh City, working side-by-side with their onshore product and consulting practice. They help ambitious clients ship production-grade AI software and rewire how they work. Across both pillars of their business - AI Advisory & Transformation, and AI Product & Engineering - AI tooling is part of how every engineer works, every day.

Their client portfolio spans wealth platforms, retail, energy, education, and engineering services, and the tech stack varies. One project might be a Spring Boot / Vue codebase, the next a .NET / Angular platform, the next a Python / React rebuild. They are looking for senior engineers who are deep enough in one stack to be productive on day one, and confident enough across the others to pick up where the project demands. AI tooling is what makes that flexibility realistic — strong engineers can ramp on a new language or framework in days rather than weeks when AI is part of how they work.

• Move between projects across our portfolio - primarily C#/.NET, Java/Spring Boot, or Python (FastAPI / Django) on the backend, with React, Angular, or Vue on the frontend. The expectation is that you can lead the work on your primary stack and contribute productively to the others.

• Pick up new languages, frameworks, and codebases quickly - using AI tooling to accelerate ramp-up and code comprehension without compromising on quality.

• Use AI coding tools every day - Claude Code, Cursor, Codex, GitHub Copilot or equivalents — as a primary part of how you ship. Not a side experiment; the way you build.

• Own quality. Review and understand every line of code you ship, AI- generated or hand-written. Catch the things the model misses, push back on poor patterns, and keep the bar high.

• Run rigorous peer code reviews, including critical review of AI-generated work - coverage that is real, tests that mean something, and patterns aligned to the codebase.

• Design and implement secure, scalable RESTful APIs.

• Work with relational databases - optimising queries, ensuring data integrity, and using ORM tooling appropriately.

• Set up and maintain CI/CD pipelines for automated testing, building and deployment (primarily GitHub Actions).

• Partner with product managers, designers and other engineers to translate business outcomes into shippable software.

• Mentor less-senior engineers on engineering craft and on getting more out of AI tooling - prompts, context, and where to be sceptical.

• Stay current on the rapidly evolving AI tooling landscape; share what you learn with the team.