Why this role exists
Away Group VN is building a new capability: an AI delivery practice that finds high-value opportunities across the business, proves them quickly as prototypes, then turns them into production systems that people rely on every day. The discovery and prototyping side of this practice is led by our AI Strategy Consultant, who works directly with business units to identify opportunities, validate them, and package each one as a handover kit: a working prototype, a specification, a presentation, and an introduction to the product owner it is being built for.
This role is the other half of the practice. You take those handover kits and turn them into production systems: hardened, integrated, deployed on cloud infrastructure you build and run, and supported for the long term. Once a product leaves the prototyping stage, you lead it. You are the first point of contact for the people who use it, and you are responsible for keeping it reliable and improving it over time.
How the practice works
• Discover and prototype (AI Strategy Consultant). Opportunities are identified with business units and validated with a working prototype. Each promoted idea arrives as a handover kit: prototype, spec, presentation, a Teams walkthrough, and an introduction to the product owner.
• Productionise and own (this role). You take the kit, clarify anything needed, and build the production system: robust code, cloud infrastructure, security, integration with existing tools and workflows, monitoring, and documentation.
• Support and evolve (this role). You own everything you ship. Users come to you first for support, fixes, and enhancement requests. The consultant can be called back in for direction changes or new scope, but in production, you lead.
• Decisions on what gets built sit with the Director and the AI Strategy Consultant. Your judgement shapes how it gets built, and your feedback from production informs what comes next.
Key responsibilities
Productionisation
• Take validated prototypes and specifications and deliver them as production-grade systems: reliable, secure, maintainable, and integrated with the tools and workflows the business already uses.
• Use AI-assisted development tooling (Claude Code and similar agentic tools) as a core part of how you work, to deliver at a pace and quality that would not be possible with traditional development alone.
• Set projects up so AI tooling can do its best work: tight feedback loops, test suites that catch failures early, and ways for agents to verify their own results before you review them.
• Write excellent documentation as you go, so every project is robust and a new developer could set it up or pick it up with little to no handover.
• Make sensible architecture and technology choices per product, favouring simplicity, maintainability, and fit with the group's existing environment.
• Clarify requirements early and directly: ask questions rather than guess, and over time learn the discovery and handover methodology so each handover needs less explanation than the last.
Infrastructure and operations
• Design, build, and run the cloud infrastructure for the products you own on platforms such as AWS, Azure, or Laravel Cloud, including deployment pipelines, environments, and access control.
• Monitor the systems you own, respond to downtime and incidents, and manage cost: hosting spend, API usage, and licensing for the products in your care.
• Maintain sensible operational hygiene: backups, secrets management, logging, and alerting.
Ownership and support
• Act as the first point of contact for users of the products you have shipped, across the group's Vietnam and Australia teams.
• Triage, fix, maintain, and upgrade the products you own; manage a backlog of enhancements with the relevant product owners.
• Work within the group's AI usage policy and data classification framework, and uphold security and privacy standards in everything you deploy.
Practice building
• Help shape the delivery standards, templates, and playbooks of the new practice as its first engineer.
• As the team grows, take on leadership: participate in hiring, onboard and mentor engineers, and lead delivery across the team's product portfolio.
• Contribute to the practice becoming a client-facing offering: repeatable delivery patterns, honest estimation, and production support that external clients would pay a retainer for.
What you bring
A note on technologies: every specific tool or platform named in this document is indicative, not mandatory. We use a variety of technologies and choose the best tool for each job. What matters is that you understand the concepts across multiple languages and platforms deeply enough to avoid the pitfalls, and that everything you build is testable, maintainable, and fit for purpose.
Essential
• Significant experience as a software engineer (typically 5+ years), with real production scars: you have built, shipped, broken, fixed, and supported systems that people depend on.
• Heavy personal investment in AI-assisted development. You use tools like Claude Code, Codex, or equivalent agentic tooling daily, and you can demonstrate that they make you dramatically more productive without compromising quality.
• Strong generalist range rather than deep specialisation in a single stack. You can move comfortably across, for example: Python, PHP/Laravel, cloud hosting (AWS or Azure), OAuth and identity, APIs, webhooks, queues, and integrating into existing systems and workflows etc.
• Proven ability to learn a new technology quickly and apply it to production standard, using AI tooling to accelerate the learning curve.
• High initiative and low supervision needs, balanced with the judgement to ask questions early instead of guessing.
• Experience running cloud infrastructure in production: deployments, monitoring, incident response, and cost awareness.
• Clear written and spoken English; comfortable working with Australian stakeholders over Teams and documenting your work well.
Highly regarded
• Experience in or adjacent to construction, architecture, BIM, CAD, or 3D visualisation workflows.
• Exposure to Microsoft Power Platform, Azure Functions, and event-driven or queue-based architectures.
• Experience with CI/CD pipelines, particularly GitHub Actions.
• Experience building on LLM APIs: agents, retrieval, structured output, evaluation, and guardrails.
• Prior team lead or mentoring experience, or clear appetite and aptitude for it.
What we offer
Interview Process: 2 online interviews (MS Teams) + 1 Technical Test
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