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Airwallex is a unified payments and financial platform serving over 250,000 global businesses including Brex, Navan, Qantas, and SHEIN. The company provides integrated solutions for business accounts, payments, spend management, treasury, and embedded finance at global scale. Valued at $11 billion and backed by leading investors including T. Rowe Price, Visa, Mastercard, and Sequoia, Airwallex operates across 27 offices with over 2,300 employees.
The Platform Engineering team is architecting next-generation foundational infrastructure, moving beyond standard pipelines to build a high-performance, distributed ecosystem powering real-time AI enablement and global financial data. The team focuses on distributed storage, stream processing, and service-layer interfaces.
In this role, you will architect and build core infrastructure components extending from foundational storage to high-availability service layers. You'll deep-dive into performance tuning and systems internals—state management, checkpointing, exactly-once semantics—to ensure millisecond-level accuracy at global scale. You'll develop and integrate the "Knowledge Platform," enabling AI-driven products through scalable vector indexing, agentic workflows, and real-time data streaming. You'll own the full software development lifecycle for high-performance distributed systems (batch and streaming) processing petabytes of data across 30+ global regions. You'll advocate for elite software engineering practices, contributing to shared tooling, SDKs, and automation frameworks that enhance company-wide engineering productivity. You'll also mentor mid-level engineers, driving project delivery through design reviews and technical leadership.
The company values builders with founder-like energy seeking real impact, accelerated learning, and true ownership. You'll tackle complex, high-visibility problems with exceptional teammates and grow your career building the future of global banking.
REQUIREMENTS:
- 5+ years of experience building and operating large-scale distributed systems or infrastructure platforms
- Deep understanding of computer science fundamentals, including distributed systems, memory management, and networking protocols
- Proficiency in Java, Kotlin, or Go with hands-on experience (or desire to deep-dive) into internals of Kafka, Flink, Spark, Kubernetes, or OLAP engines
- Proven track record of taking 0-1 ownership of complex technical challenges from initial design to production stability
- Intrinsic motivation to explore emerging tech in AI/ML infrastructure and real-time systems to create tangible business impact
