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Airwallex

Senior Software Engineer, Infrastructure (Data & AI)

Airwallex is hiring a Senior Software Engineer, Infrastructure (Data & AI) in Seoul, South Korea. Level rates it ; you can apply on Airwallex.

Level's read on this job

  • Level rates this software engineer role Builds AI ●●●●: the job is building AI systems.
  • Tools and skills the posting cites include vLLM, Kubernetes and Kafka.
  • Level classifies it as a senior role.
  • Level lists 483 other open roles at Airwallex.

AI in this role

Senior Infrastructure Engineer needed to build and operate scalable data and AI platforms and infrastructure at Airwallex.

vLLMKubernetesKafkaSparkFlinkAWS
devopssreplatform-engineeringinfrastructuredata-pipelines

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 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.

This role is based in Seoul, South Korea.

Address: Units 1006, Partners Tower, 83 Gasan digital 1-ro, Geumcheon-gu, Seoul, Republic of Korea, 08589 서울 금천구 가산디지털1로 83, 1006 호(가산동, 파트너스타워)

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.

Applicant Safety Policy: Fraud and Third-Party Recruiters

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 opportunity

Airwallex 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.

How we rate this

Senior Software Engineer, Infrastructure (Data & AI) at Airwallex rates 80 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

DevOpsSrePlatform EngineeringInfrastructureData PipelinesvLLMKubernetesKafka

Also common in software engineer jobs at this level

Pay

Typical software engineer job
$167k

This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs

Questions you could be asked

  1. Tell me about a project where devops was part of your work. What did you do?
  2. Tell me about a project where sre was part of your work. What did you do?
  3. Tell me about a project where platform engineering was part of your work. What did you do?
  4. Tell me about a project where infrastructure was part of your work. What did you do?
  5. Tell me about a project where data pipelines was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: DevOps, Sre, Platform Engineering, Infrastructure, and Data Pipelines. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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