Airwallex is the AI-native financial operating system for a real-time, intelligent economy. More than 676,000 businesses, including McLaren Racing, Qantas, SHEIN, and TikTok, use us, directly or through our platform partners, to run their financial operations or build and monetize financial products of their own.
We started in Melbourne in 2015 to build the infrastructure global commerce runs on. We're the regulated backbone behind global payments: not by accident, but by design. A decade plus, 85+ licenses, and a financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific.
We're co-headquartered in San Francisco and Singapore, with more than 2,300 people across 27 offices. We hire builders with founder-level energy, people who move fast with good judgment, dig in with real curiosity, and make calls from first principles rather than waiting to be told what to do. Read our operating principles to see it in full.
About the team
You’d be joining the team building Airwallex’s AI tooling platform. A product that helps employees turn ideas into working apps, dashboards, and workflow tools faster, with strong focus on platform engineering, integrations, security, and scale.
Your role will be delivering AI Tooling being leveraged by all Airwallex employees. You’ll have the opportunity to partner with internal teams to help identify projects that can drive impact – like building internal automation tooling, owning our terabyte-scale log pipelines, and using AI to streamline how our team operates.
We’re not tied to specific projects, languages, and technology – we rely on smart people diving deep to find the best solutions to hard problems. You’ll also be mentoring junior team members and continuing to grow our world-class engineering team.
This role is based in San Francisco, or Melbourne, or Sydney
Responsibilities:
Lead the development of AI tools and applications, from inception to implementation.
Support incident response efforts by building ad-hoc tools for threat hunting, remediation and scanners.
Build, monitor, and maintain underlying infrastructure, including Kubernetes clusters, serverless workloads, and ETL pipelines.
Sit with engineers to identify opportunities for automation and tooling development
Partner with product engineering teams to drive security outcomes – such as automation for patching, and development of gateways and other services to decrease risk.
Mentor and help grow other Software Engineers in the team.
We’re looking for people who meet the minimum qualifications for this role. The preferred qualifications are great to have, but are not mandatory.
Minimum qualifications:
Bachelor’s degree in Computer Science, Information Security, or a related field.
8+ years of experience as a Software Engineer.
Experience with production code bases
Experience with at least one scripting language (e.g. Python) and one systems programming language (eg. Golang, C/C++)
Experience with modern cloud infrastructure, including data pipelines, serverless workloads, and Kubernetes
Proven experience working autonomously on projects – delivering them to a high quality and on time.
Excellent communication and interpersonal skills, with the ability to work effectively with both technical and non-technical stakeholders.
Ability to dive deep to find the best solution to a problem
Obsessive curiosity and a willingness to ask questions, gather context, and learn
Preferred qualifications:
Experience working in a high-growth tech company.
Hands on experience with AI – specifically leveraging AI to build applications
Experience maintaining Linux operating systems
To protect you from recruitment scams, please be aware that Airwallex will not ask for bank details, sensitive ID numbers (i.e. passport), or any form of payment during the application or interview process. All official communication will come from an @airwallex.com email address. Please apply only through careers.airwallex.com or our official LinkedIn page.
Airwallex does not accept unsolicited resumes from search firms/recruiters. Airwallex will not pay any fees to search firms/recruiters if a candidate is submitted by a search firm/recruiter unless an agreement has been entered into with respect to specific open position(s). Search firms/recruiters submitting resumes to Airwallex on an unsolicited basis shall be deemed to accept this condition, regardless of any other provision to the contrary.
Equal opportunityAirwallex is proud to be an equal opportunity employer. We value diversity and anyone seeking employment at Airwallex is considered based on merit, qualifications, competence and talent. We don’t regard color, religion, race, national origin, sexual orientation, ancestry, citizenship, sex, marital or family status, disability, gender, or any other legally protected status when making our hiring decisions. If you have a disability or special need that requires accommodation, please let us know.
Airwallex San Francisco, California, USA Office
Airwallex San Francisco, US Office
188 Spear Street’s superior location is two blocks from the Embarcadero, the promenade running along the SF waterfront, and offers exceptional views and convenience through its easy access to BART, Muni, ferries, the Transbay Terminal, the Bay Bridge and all major freeways.
Sales





This is not just another sales role. It is a chance to sell a proven global platform, shape how we win across the Americas, and do career-defining work. You get the product, the territory, and the support to build real momentum.
AI Engineering



Our SF AI Engineering team at Airwallex is building production-grade AI that automates the hardest parts of global finance — from payments and onboarding to reconciliation, bookkeeping, and tax. Sitting on top of our proprietary global payments infrastructure and massive real-time transaction datasets, we design and ship vertical AI systems — from LLM-powered copilots and agentic workflows to fine-tuned models — that reach customers quickly and at scale. We’re a small, senior, zero-ego group with high ownership: engineers work end to end from problem framing and experimentation through to deployment and evals, using the right tool for the job to turn deep AI work into visible, shipped impact.
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