Senior Software Engineer, Data Platform & AI Enablement
About The Position
The Senior Software Engineer will help build Airwallex’s Knowledge Platform, the infrastructure connecting company data, real-time systems, and AI capabilities. The role involves creating distributed foundations for reliable data processing, intelligent products, and global financial infrastructure, including core infrastructure from foundational storage through high-availability service layers. The engineer will lead technical decisions and custom development for high-performance distributed systems supporting real-time AI enablement and global financial data. They will improve performance across state management, checkpointing, memory management, and exactly-once semantics; build and integrate scalable vector indexing, agentic workflows, and real-time data streaming; and own the software development lifecycle for batch and streaming systems processing petabytes of data across more than 30 global regions. The role also contributes shared tooling, SDKs, and automation frameworks, and provides technical guidance and mentorship. The Knowledge Platform spans technologies and capabilities including Databricks, ClickHouse, Spark, Kafka, real-time analytics, knowledge retrieval and indexing, model infrastructure, agent capabilities, and AI interaction history. The team is developing evaluation, annotation, feedback, governance, permission, and freshness frameworks to operate AI reliably at global financial scale. The position works from Airwallex’s Seattle office three days per week.
Requirements
- At least 5 years of experience building and operating large-scale distributed systems or infrastructure platforms.
- Strong understanding of computer science fundamentals, including distributed systems, memory management, and networking protocols.
- Proficiency in Java, Kotlin, or Go.
- Experience taking complex technical challenges from initial design through production stability.
- Experience with performance tuning and systems internals, including state management, checkpointing, and exactly-once semantics.
- Track record of technical leadership through architecture decisions, design reviews, or mentorship.
- Curiosity about AI/ML infrastructure and real-time systems, with a focus on tangible business impact.
Nice To Haves
- Hands-on experience with, or a strong desire to work deeply in, technologies such as Kafka, Flink, Spark, Kubernetes, or OLAP engines.
Responsibilities
- Architect and build core infrastructure components, from foundational storage through high-availability service layers.
- Lead technical decisions and custom development for high-performance distributed systems supporting real-time AI enablement and global financial data.
- Improve system performance across state management, checkpointing, memory management, and exactly-once semantics.
- Build and integrate the Knowledge Platform, including scalable vector indexing, agentic workflows, and real-time data streaming.
- Own the full software development lifecycle for batch and streaming systems processing petabytes of data across more than 30 global regions.
- Develop shared tooling, SDKs, and automation frameworks to improve engineering productivity and quality.
- Mentor engineers through design reviews, technical guidance, and delivery leadership.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
