Senior Software Engineer, Data and AI Infrastructure
Senior engineer building Airwallex's data and AI platform infrastructure: designing and operating distributed systems for high-throughput streaming and batch processing (Kafka, Spark, Flink), evolving Kubernetes/cloud foundations, and building AI traffic management and model-serving layers. Hybrid role based in Seattle, WA.
- Compensation
- $150K–$245K / yr
- Location
- US - Seattle
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Software engineering
- Posted
Skills
Must have
- 5+ years in DevOps, SRE, or platform engineering, owning production systems end to end
- Strong experience designing, operating, and troubleshooting production Kubernetes environments
- Experience with distributed data infrastructure (Kafka, Spark, or Flink) or AI infrastructure such as AI gateways or model-routing platforms
- Hands-on experience with at least one major public cloud platform (AWS, Google Cloud, or Microsoft Azure)
- Strong knowledge of cloud and container networking (DNS, load balancing, ingress, service discovery, TLS, routing, network security)
- Proficiency in one or more of Go, Python, or Java with production software experience
- Solid understanding of distributed-systems concepts (availability, consistency, fault tolerance, backpressure, horizontal scalability)
- Experience operating critical infrastructure using infrastructure-as-code, automated delivery, and modern observability practices
- Strong debugging skills across multiple layers of complex systems
- Clear communication and cross-disciplinary collaboration skills
- Ownership mindset: identify important problems and drive them to resolution
Nice to have
- Platform engineering experience building internal developer platforms or paved-road workflows
- 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 cost efficiency of large-scale data processing or AI inference workloads
- Contributions to infrastructure, data-platform, Kubernetes, or AI-serving open-source projects
Full description
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 to see it in full.
How you'll make impact
You’ll design, build, and operate highly available data and AI infrastructure on Kubernetes and public cloud platforms. You’ll develop scalable platforms for streaming, batch processing, and real-time data workloads using technologies such as Kafka, Spark, and Flink, while building AI infrastructure including gateways, model-routing layers, traffic management, rate limiting, authentication, observability, and usage controls.
- Improve the scalability, reliability, efficiency, and cost visibility of production data and AI workloads.
- Build self-service capabilities that help data, AI, and application teams deploy and operate workloads safely and independently.
- Partner across engineering to turn emerging data and AI requirements into durable platform capabilities.
- Deliver the technical foundations for the next generation of data and AI infrastructure.
- Drive platform capabilities that help engineering teams operate critical workloads with greater independence.
You’ll work from our Seattle office three days a week.
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.