Senior Software Engineer, Infrastructure (Data & AI)

About Airwallex

Airwallex is the AI-native financial operating system for a real-time, intelligent economy. More than 675,000 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 2,700 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](https://www.airwallex.com/en-us/operating-principles) to see it in full.

How you'll make impact

You'll build and operate the infrastructure that powers Airwallex's data and AI platforms. You'll design highly available systems on Kubernetes and public cloud platforms, and develop scalable foundations for streaming, batch processing, and real-time workloads using technologies such as Kafka, Spark, and Flink.

• Build and operate highly available data and AI infrastructure on Kubernetes and public cloud platforms.
• Develop scalable foundations for streaming, batch processing, and real-time data workloads using technologies such as Kafka, Spark, and Flink.
• Evolve AI infrastructure, including AI gateways, model-routing layers, traffic management, rate limiting, authentication, observability, and usage controls.
• Deliver self-service capabilities that help data, AI, and application teams deploy and operate workloads safely and independently.
• Partner across engineering disciplines to turn emerging data and AI requirements into durable platform capabilities.
• Improve the scalability, reliability, and efficiency of our data and AI infrastructure, while reducing the operational effort required to deploy and manage workloads.

What we're looking for

Essentials

• 5+ years in DevOps, SRE, or platform engineering, owning production systems end to end.
• Strong experience designing, operating, and troubleshooting production Kubernetes environments.
• Experience building or operating distributed data infrastructure with technologies such as Kafka, Spark, or Flink, or experience developing AI infrastructure such as AI gateways or model-routing platforms.
• Hands-on experience with at least one major public cloud platform, such as AWS, Google Cloud, or Microsoft Azure.
• Strong knowledge of cloud and container networking, including DNS, load balancing, ingress, service discovery, TLS, routing, and network security.
• Proficiency in one or more of Go, Python, or Java, with experience writing maintainable production software.
• A solid understanding of distributed-systems concepts, including availability, consistency, fault tolerance, backpressure, and horizontal scalability.
• Experience operating critical infrastructure using infrastructure-as-code, automated delivery, and modern observability practices.
• Strong debugging skills and the ability to work methodically across multiple layers of a complex system.
• Clear communication skills and a track record of collaborating effectively across engineering disciplines.
• An ownership mindset: you identify important problems, drive them to resolution, and improve the underlying system rather than treating symptoms.

Preferred

• Platform engineering experience, particularly building internal developer platforms or paved-road workflows used by multiple engineering teams.
• Hands-on experience with serving technologies such as SGLang, vLLM, or NVIDIA Triton Inference Server.
• Knowledge of GPU scheduling, batching, model parallelism, memory management, autoscaling, and inference-performance optimization.
• Experience improving the cost efficiency of large-scale data processing or AI inference workloads.
• Contributions to infrastructure, data-platform, Kubernetes, or AI-serving open-source projects.

You'll thrive here if

• You're comfortable owning the roadmap yourself.
• You own the outcome and you don't wait for permission to fix what's broken.
• You're comfortable with ambiguity. Give you a problem, not a prescription, and you'll run with it.
• You say what you mean. You're direct, but you lead with respect.
• You connect dots across functions and hold the big picture without losing grip on the details.

Learn more about your team

The Infrastructure & Productivity team at Airwallex builds the technical foundation that allows our global engineering organization to scale. Our customers are our fellow engineers, and our mission is to make their daily work faster, safer, and more effective by managing the core platforms everyone relies on, from Kubernetes and Kafka to CI/CD pipelines and observability systems. The real challenge lies in keeping these global systems highly reliable and secure while simultaneously optimizing cloud costs, automating manual support, and driving standardization without slowing down product delivery. We operate under the philosophy that best practices should be the path of least resistance, not a forced mandate. If you're a systems thinker who wants to work close to the core of the company and directly shape how we build, deploy, and scale software worldwide, this is where that work happens.