Senior Software Engineer, Data and AI Infrastructure

The role

You will design, build, and operate highly available data and AI infrastructure on Kubernetes and public cloud platforms. You will develop scalable platforms for streaming, batch processing, and real-time data workloads.

What you will do

• Improve the scalability, reliability, efficiency, and cost visibility of production data and AI workloads.
• Build self-service capabilities for data, AI, and application teams.
• 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.

Required qualifications

• 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 platf
• 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.

Nice to have

• 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.

About the company

Airwallex is the AI-native financial operating system for a real-time, intelligent economy. The company provides financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific.