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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer, Data and AI Infrastructure - **Company:** Airwallex US, LLC - **Location:** Seattle, WA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, User Authentication, Microsoft Azure, Batch Processing, Big Data, Cloud Computing, Software Debugging, DevOps, Distributed Data Store, Domain Name System (DNS), Memory Management, Fault Tolerance, Python (Programming Language), Network Security, Routing, Open Source Technology, Operational Databases, Performance Tuning, Systems Development Life Cycle, Real-Time Operating Systems, Service Discovery, Software Engineering, Data Streaming, AI Infrastructure, Transport Layer Security, Google Cloud, Load Balancing, Cloud Platform System, Autoscaling, System Availability, Apache Spark, Parallel Computation, Rate Limiting, Kubernetes, Apache Flink, SGLang, Real Time Data, Apache Kafka, Triton Inference Server, VLLM, Model Inference - **Published:** November 11, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-software-engineer-data-and-ai-infrastructure-seattle-wa--88a921e2-9e49-4f40-934a-a300be403f96 ## About the Role Software Engineering, Artificial Intelligence (AI), Financial Operations, Artificial Intelligence (AI), Financial Systems, Realtime Operating System, Scalable System Development, Public Cloud, High Availability, Authentication, * 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., * 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're comfortable with ambiguity. Give you a problem, not a prescription, and you'll run with it. * You own the outcome and you don't wait for permission to fix what's broken. * You're comfortable operating across time zones with a globally distributed team, including colleagues based in APAC and EMEA. * You say what you mean. You're direct, but you lead with respect. ## Description 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., 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.