Staff/Engineering Lead, Data&AI Infrastructure

Airwallex
SG - SingaporePosted 24 March 2026

Job Description

Staff/Engineering Lead, Data&AI Infrastructure ABOUT AIRWALLEX Airwallex is the only unified payments and financial platform for global businesses. Powered by our unique combination of proprietary infrastructure and software, we empower over 200,000 businesses worldwide – including Brex, Rippling, Navan, Qantas, SHEIN and many more – with fully integrated solutions to manage everything from business accounts, payments, spend management and treasury, to embedded finance at a global scale. 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 https://www.airwallex.com/us/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. About The Team As the engineering organization matures, the infrastructure teams are the key to Airwallex's ability to build a globally distributed platform, increase engineer productivity and ensure effective use of resources. Our teams work to provide the best possible experience for our developers and customers while providing a safe and secure environment to ensure that our financial solutions are always available. What You’ll Do The Data+AI Infra team is tasked with providing our data engineering and analytics teams with the right tools. You will be responsible for developing and maintaining the data infrastructure. Additionally, you will create and enhance tooling and platforms to empower the engineering team with improved self-service capabilities. This role is based in Singapore. Responsibilities - Provide technical leadership and direction to a team of engineers based in Singapore. - Design and implement a robust and scalable data infrastructure tailored to meet different needs of the engineering team. - Design and develop scalable software applications and systems that provide strong self-service capabilities and ensure robust architecture and maintainability. - Conduct comprehensive testing and quality assurance to identify and rectify errors, ensuring the software aligns with quality standards and functions effectively. - Perform ongoing maintenance and troubleshooting for deployed software, implementing updates and enhancements to improve functionality and address evolving needs. - Leverage AI-assisted tools (e.g., code assistants, observability copilots, knowledge/search tools) to accelerate development, improve quality, and create reusable workflows and best practices for the wider team. - Proactively identify, frame, and solve ambiguous problems across data and platform domains, turning loosely defined requirements into clear technical plans and incremental deliverables. - Collaborate effectively with cross-functional teams (data, platform, AI, security, and product) to ensure project alignment and timely delivery. - Engage in continuous learning to stay abreast of emerging technologies, programming languages, development met ... (truncated, view full listing at source)
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