Senior Software Engineer, Infrastructure (Data & AI)
Infrastructure Engineer · Senior · Full Time
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Role
What you'll do.
Senior Software Engineer, Infrastructure role at Airwallex, the AI-native financial operating system serving 676,000+ businesses globally. Design and operate distributed systems supporting high-throughput data processing, real-time workloads, and production AI applications on Kubernetes and public cloud platforms. Requires 5+ years in DevOps/SRE/platform engineering with strong Kubernetes expertise, distributed data infrastructure experience (Kafka, Spark, Flink), and proficiency in Go, Python, or Java.
Responsibilities
- Design and operate highly available distributed systems: Design, build, and operate highly available data and AI infrastructure on Kubernetes and public cloud platforms, ensuring scalability and reliability for enterprise-grade workloads serving 676,000+ businesses globally.
- Develop scalable streaming and batch processing platforms: Create and maintain scalable platforms for streaming, batch processing, and real-time data workloads using distributed technologies such as Apache Kafka, Apache Spark, and Apache Flink, optimizing for throughput and latency requirements.
- Build AI infrastructure and model serving systems: Build and evolve AI infrastructure including AI gateways, model-routing layers, traffic management, rate limiting, authentication, observability, and usage controls to support production AI applications at scale.
- Develop self-service platform capabilities: Develop self-service capabilities that enable data, AI, and application engineering teams to deploy and operate workloads safely and independently, reducing operational friction and accelerating development velocity.
- Partner across engineering disciplines: Collaborate with application, data, machine learning, security, and infrastructure teams to translate emerging data and AI requirements into durable, reusable platform capabilities that serve as the foundation for company growth.
- Improve system observability and efficiency: Establish visibility into system performance, reliability, capacity, and cost, implementing observability practices and optimizing resource utilization across data and AI infrastructure.
Qualifications
What we look for.
Technical
Kubernetes expertise
Strong experience designing, operating, and troubleshooting production Kubernetes environments at scale, including cluster architecture, workload management, and container orchestration.
Distributed data infrastructure
Experience building or operating distributed data infrastructure with technologies such as Apache Kafka, Apache Spark, or Apache Flink, understanding streaming and batch data architecture patterns.
Cloud platform proficiency
Hands-on experience with at least one major public cloud platform (AWS, Google Cloud, or Microsoft Azure), including networking, storage, compute, and infrastructure-as-code tools.
Cloud and container networking
Strong knowledge of cloud and container networking concepts including DNS, load balancing, ingress controllers, service discovery, TLS/SSL, routing, network policies, and security best practices.
Infrastructure-as-code and automation
Experience operating critical infrastructure using infrastructure-as-code practices, automated delivery pipelines, CI/CD systems, and modern observability platforms for production environments.
Distributed systems fundamentals
Solid understanding of distributed-systems concepts including availability, consistency models, fault tolerance, backpressure, horizontal scalability, and architectural trade-offs.
Multi-layer debugging and troubleshooting
Strong debugging skills and ability to work methodically across multiple layers of complex systems, from application code through infrastructure and networking.
Education
Computer Science foundation or equivalent
Bachelor's degree in Computer Science, Software Engineering, or related field, or equivalent professional experience demonstrating strong foundational knowledge in software systems.
Experience
5+ years in DevOps, SRE, or platform engineering
Minimum 5 years of hands-on experience in DevOps, Site Reliability Engineering (SRE), or platform engineering roles, owning production systems end-to-end and managing infrastructure at scale.
Production infrastructure ownership
Track record of designing, deploying, and maintaining production infrastructure systems, with demonstrated responsibility for system reliability, performance, and operational excellence.
Cross-functional collaboration
Proven ability to collaborate effectively across engineering disciplines, including application developers, data engineers, ML engineers, and security teams in complex technical environments.
Skills
Required
Go
Proficiency in Go programming language for building efficient, concurrent infrastructure software and automation tools.
Python
Strong Python skills for scripting, infrastructure automation, and data-processing infrastructure development.
Java
Proficiency in Java for building scalable distributed systems and integrating with big data frameworks like Spark.
Kubernetes administration
Hands-on expertise in Kubernetes cluster setup, configuration, troubleshooting, and operational management in production environments.
Apache Kafka
Practical experience with Apache Kafka for building distributed event streaming platforms and real-time data pipelines.
Cloud platforms (AWS/GCP/Azure)
Competency with major cloud providers' infrastructure services, including compute, networking, storage, and managed services relevant to data and AI workloads.
Systems troubleshooting
Ability to diagnose and resolve complex issues across application, infrastructure, and network layers using systematic debugging approaches.
Technical communication
Clear verbal and written communication skills for documenting infrastructure decisions, mentoring team members, and collaborating across technical and non-technical stakeholders.
Preferred
AI/ML infrastructure experience
Nice to haveHands-on experience with serving technologies such as SGLang, vLLM, or NVIDIA Triton Inference Server for production AI model deployment.
GPU scheduling and optimization
Nice to haveKnowledge of GPU scheduling, model batching strategies, model parallelism, memory management, autoscaling patterns, and inference-performance optimization techniques.
Platform engineering and IDP
Nice to haveExperience building internal developer platforms (IDPs) or paved-road workflows that enable multiple engineering teams to self-serve and operate infrastructure independently.
Apache Spark and Flink
Nice to haveExperience with Apache Spark for large-scale batch processing or Apache Flink for stream processing, including optimization and operational best practices.
Cost optimization
Nice to haveDemonstrated experience improving cost efficiency of large-scale data processing or AI inference workloads, including resource optimization and waste reduction strategies.
Open-source contributions
Nice to haveContributions to infrastructure, data-platform, Kubernetes, or AI-serving open-source projects demonstrating deep expertise and community engagement.
Observability and monitoring
Nice to haveAdvanced expertise with observability tools and practices for monitoring distributed systems, implementing comprehensive logging, metrics, and tracing.
Infrastructure security
Nice to haveKnowledge of infrastructure security best practices, authentication mechanisms, network policies, and compliance requirements in cloud-native environments.
Tech stack
Languages
Frameworks
Databases
Tools
Other
Compensation
Pay and benefits.
Base·USD 120,000 – 180,000
Equity·Stock options
Benefits
Equity and ownership
Participate in Airwallex's growth through stock options and equity grants, aligning personal success with company success.
Professional development
Access to continuous learning opportunities, technical conferences, training budgets, and opportunities to contribute to open-source projects.
Global career opportunities
Work for a globally distributed fintech leader with 2,300+ employees across 27 offices, enabling internal mobility and exposure to international markets.
Challenging technical problems
Solve complex infrastructure challenges at scale, working on systems that support 676,000+ businesses globally and serving multiple currency and regulatory jurisdictions.
Cross-functional collaboration
Collaborate with world-class data engineers, AI/ML engineers, application engineers, and security teams on cutting-edge fintech infrastructure.
Impact on financial infrastructure
Contribute to the regulated backbone powering global commerce, supporting companies like McLaren Racing, Qantas, SHEIN, and TikTok.
Flexible work environment
Work with a founder-level energy culture that values builder mentality, good judgment, curiosity, and first-principles thinking.
Comprehensive health and wellness
Competitive health insurance, wellness programs, and support for work-life balance in a fast-paced fintech environment.
Process
Interview steps.
- 01
Initial screening
Phone or video screening with a recruiter to discuss your background, infrastructure experience, and alignment with Airwallex's culture of builder-level energy and first-principles thinking.
- 02
Technical assessment
Focused technical interview exploring your experience with Kubernetes, distributed systems, and production infrastructure challenges. Expect discussions on past projects, architectural decisions, and problem-solving approaches.
- 03
Infrastructure design deep-dive
Detailed technical conversation with engineering leaders about designing scalable data and AI infrastructure, covering system design, trade-offs, and operational considerations for high-throughput workloads.
- 04
Coding or systems design exercise
Practical technical exercise focused on infrastructure problem-solving, system design, or coding capabilities in Go, Python, or Java. Emphasis on production-grade thinking and practical constraints.
- 05
Cross-functional team interviews
Conversations with data engineers, AI/ML engineers, or platform team members to assess collaboration style and understand how you'll work across engineering disciplines.
- 06
Leadership alignment
Final discussion with engineering leadership or team manager covering long-term vision, technical direction, team dynamics, and your career growth within Airwallex's global infrastructure organization.
Full posting
Original listing.
About Airwallex
Airwallex is the AI-native financial operating system for a real-time, intelligent economy. More than 676,000 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 2,300 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.
About The Team
We are looking for a Senior Software Engineer to build the infrastructure that powers our data and AI platforms.
You will design and operate distributed systems that support high-throughput data processing, real-time workloads, and production AI applications. This includes evolving our Kubernetes and cloud foundations, improving the reliability and scalability of platforms such as Kafka, Spark, and Flink, and building infrastructure for AI traffic management and model serving.
This is a high-impact role for an engineer who enjoys solving complex infrastructure problems, writing production software, and giving other engineering teams reliable self-service platforms. You will work across application, data, machine learning, security, and infrastructure teams to establish the technical foundations for the company’s next stage of growth.
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 You’ll Do
Design, build, and operate highly available data and AI infrastructure on Kubernetes and public cloud platforms.
Develop scalable platforms for streaming, batch processing, and real-time data workloads using technologies such as Kafka, Spark, and Flink.
Build and evolve AI infrastructure, including AI gateways, model-routing layers, traffic management, rate limiting, authentication, observability, and usage controls.
Develop self-service capabilities that enable data, AI, and application teams to deploy and operate workloads safely and independently.
Partner with engineering teams to translate emerging data and AI requirements into durable platform capabilities.
Who You Are
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.
Especially Valuable Experience
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.
What Success Looks Like
Delivered meaningful improvements to the scalability, reliability, or efficiency of our data and AI infrastructure.
Reduced the operational effort required to deploy and manage data or AI workloads.
Improved visibility into system performance, reliability, capacity, and cost.
Established reusable platform capabilities adopted by engineering teams.
Helped define the technical direction for our next generation of data and AI infrastructure.
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.
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