Staff Software Engineer, Infra Productivity
Indexed description
Proudly founded in Melbourne, we have a team of over 2,000 of the brightest and most innovative people in tech across 26 offices around the globe. Valued at US$8 billion and backed by world-leading investors including T. Rowe Price, Visa, Mastercard, Robinhood Ventures, Sequoia, Salesforce Ventures, DST Global, and Lone Pine Capital, Airwallex is leading the charge in building the global payments and financial platform of the future. If you’re ready to do the most ambitious work of your career, join us.
Attributes We Value
We hire successful builders with founder-like energy who want real impact, accelerated learning, and true ownership. You bring strong role-related expertise and sharp thinking, and you’re motivated by our mission and operating principles. You move fast with good judgment, dig deep with curiosity, and make decisions from first principles, balancing speed and rigor.
You're humble and collaborative; turn zero‑to‑one ideas into real products, and you “get stuff done” end-to-end. You use AI to work smarter and solve problems faster. Here, you’ll tackle complex, high‑visibility problems with exceptional teammates and grow your career as we build the future of global banking. If that sounds like you, let’s build what’s next.
Responsibilities
As a Staff Software Engineer, you will provide the technical leadership and architectural vision for the Productivity team. The team is building the infrastructure for an agent-centric software development lifecycle — a paradigm shift where AI agents are the primary operators across the full product development cycle, and humans set direction, define constraints, and review outcomes. You will own the technical strategy across our core platforms: AirDev (AI agent execution engine), AirForge (AI-powered application factory), and Quartermaster (agent workforce governance), shaping how hundreds of engineers — and their AI counterparts — build software at Airwallex.
What You Will Do
- Agentic Platform Architecture: Design and evolve the architecture for AirDev, our platform for running autonomous AI agents that execute software development tasks end-to-end — from story creation through code generation, testing, and merge request delivery.
- Agent Governance & Orchestration: Architect Quartermaster, the control plane that provisions, constrains, and manages autonomous agent workflows (CREWs) across the organization, including safety, auditability, and progressive autonomy controls.
- AI Application Infrastructure: Lead the technical direction for AirForge, a containerized AI-powered application factory that enables developers and non-engineers to generate, run, and share web applications from natural language — including its desktop runtime, container orchestration, and MCP-based integration layer.
- System Design & Integration: Design event-driven architectures connecting AI agents with enterprise systems (GitLab, Jira, Confluence, Slack) via Kafka pipelines, webhooks, and APIs — enabling closed-loop automation across the full product development lifecycle.
- Technical Leadership: Define domain-level technical roadmaps, review RFCs, and mentor senior engineers. Raise the bar on architecture quality, security posture, and operational maturity across the team's platform services.
- A minimum of 8 years of professional software engineering experience with a track record of technical leadership.
- Strong system design skills — experience architecting distributed, event-driven platforms with high availability and scalability requirements.
- Proficiency in Python and/or TypeScript/Node.js. Experience with frameworks like FastAPI, Next.js, or Express.
- Hands-on experience with Kubernetes, Docker, and cloud platforms (GCP preferred; AWS or Azure also relevant).
- Excellent communication and stakeholder management skills, with the ability to influence technical strategy across a global engineering organization.
- Experience building AI/LLM-powered developer tools, agent frameworks, or autonomous systems.
- Familiarity with LLM integration patterns — prompt engineering, context engineering, tool use, MCP (Model Context Protocol), or agent orchestration frameworks.
- Experience with event-driven architectures (Kafka), GitOps (ArgoCD, Helm), and infrastructure-as-code (Terraform).
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