• We’re building Unloan through smarter, AI-powered software and automation.
• You have strong TypeScript, full-stack and Linux skills with end-to-end ownership.
• Together we solve complex problems and make engineering faster, safer and smarter.

Do work that matters:

As a Senior Software Engineer in Unloan’s Platform Team , you’ll be a software engineer first, designing, building and owning production software end to end. You’ll work across the full stack, building applications, APIs, integrations and automation using technologies such as TypeScript, Node.js and Python, while taking what you build all the way through testing, deployment and production support. You’ll solve complex engineering problems, integrate distributed systems and use AI-assisted development to create smarter, more automated ways of working. Alongside application engineering, you’ll also support the platform services your software depends on, giving you exposure across cloud, containers, Linux and modern delivery tooling.

What makes this role exciting is the breadth of problems you’ll get to solve. You might build an AI-powered workflow one day, integrate engineering and security systems the next, then dive into a production issue across application code, APIs or Linux-based platform services. You’ll help modernise CI/CD, automate operational processes and improve the reliability and security of the engineering environment, with Azure, GitHub Actions, Terraform or Bicep, containers and observability forming part of the wider landscape.

It’s an opportunity to own software from idea through to production, while developing the platform capabilities that help Unloan’s engineers build, release and operate software faster and more safely. 

See yourself in our team:  

Unloan is a fully digital home loan platform backed by CBA. We believe operational problems are engineering problems waiting to be solved. Our Platform team is a small group of senior engineers with the autonomy to find those problems and fix them properly, whether that means writing application code, integrating APIs, debugging infrastructure, improving security or replacing a manual banking process with reliable automation.

We’re also AI-native in how we engineer. We don’t just use AI to write code, review changes and solve problems faster, we build agents and automated workflows ourselves. Curiosity and experimentation are expected, as is the ability to dive into unfamiliar systems, understand how they really work and challenge existing assumptions. You’ll help us push what’s possible within a banking control environment, building software that makes engineering safer, faster and increasingly autonomous. 

We’re interested in hearing from people who: 

• Build production software using TypeScript (essential) and or Nodejs, Python, or Go.  
• Have strong engineering background and remain hands-on with production code.
• Are a full-stack engineer who can work across front-end, back-end, APIs, services and platform integrations.
• Take full-cycle, end-to-end ownership, from design and development through deployment, production support and continuous improvement.
• Bring strong Linux experience, including troubleshooting applications, services and production environments.
• Use AI-assisted development confidently and can build, review, test and safely productionise AI-powered agents and workflows.
• Can connect complex systems using APIs, events, queues and distributed integration patterns.
• Excel at debugging complex production issues across application, network and platform layers, while automating repetitive operational work.
• Bring experience across technologies (but  not limited too) such as Azure, GitHub Actions, containers, Terraform/Bicep, observability, networking and security automation.

Tech skills:

We don't expect you to know everything, but experience in several of the following will set you up for success:

• Operating system: Linux
• Front end: TypeScript
• Back end: TypeScript , Node.js, Python, Go,
• API: RESTful APIs
• Distributed systems: Events, queues, distributed system patterns, Kubernetes
• AI development: AI-assisted development tools, AI-generated code review and testing
• AI engineering: AI-powered tooling, agents, MCP servers, LLM-backed workflows
• Cloud: Azure (prefer), AWS
• Containers: Containers, container-based platforms
• Infrastructure as code: Bicep, Terraform
• CI/CD: GitHub Actions
• Observability: Monitoring, operational tooling
• Security: Security controls, security automation
• Networking: DNS, TLS, routing, network security
• Production engineering: Debugging, root-cause analysis, production support
• Automation: Operational automation, business process automation
• Engineering: Production code, code reviews, end-to-end system ownership