Staff Software Engineer, Data Platform

Airwallex is evolving its data and AI platforms into an agent-ready foundation for company-wide decision-making and measurable business impact. As a Staff Software Engineer, you’ll shape the architecture and technical direction that makes this possible.

• Own the strategy, architecture, development, and operation of Airwallex’s data and AI platforms, turning data and AI capabilities into measurable business impact.
• Identify and solve company-wide challenges through scalable data platform solutions, influencing technical direction across multiple teams.
• Shape the evolution of our data ecosystem into AI agent-ready infrastructure that supports real-time performance, analytics, natural-language querying, and data-driven decision-making.
• Raise the bar for technical excellence across data platforms by solving complex problems hands-on, advocating for strong engineering practices, and mentoring engineers and technical leaders., You’ll build the platform end to end, from core technologies such as Databricks, Clickhouse, Spark, and Kafka to real-time analytics, knowledge retrieval and indexing, model infrastructure, agent capabilities, and AI interaction history. You’ll also develop the evaluation, annotation, feedback, governance, permission, and freshness frameworks required to operate AI reliably at global financial scale.

Our mission is making this ecosystem truly agent-ready. That means enabling teams to explore data through natural language, investigate business drivers in real time, and give AI systems secure access to the context and capabilities they need to support decisions and execute workflows.

If you want to build the foundation that turns Airwallex’s data into knowledge, knowledge into intelligence, and intelligence into measurable business impact, this is where that work happens.

Software Engineering, Financial Operations, Artificial Intelligence (AI), Financial Systems, Realtime Operating System, MCP - Microsoft Certified Professional, Data Management, Ecosystems, Systems Administration/Management, Software Engineering, * 8+ years of experience in data platforms or an equivalent combination of professional experience and academic exposure in a quantitative field.

• Experience leading company-wide initiatives across multiple teams or influencing technical roadmap planning.
• A track record of collaborating with diverse teams and stakeholders to drive tangible business outcomes.
• The ability to balance execution and velocity with in-depth research, statistical understanding, and scalable system design.
• Experience mentoring and investing in the development of scientists, engineers, and peers.
• Technical leadership experience across significant data platform projects, including ETL frameworks, metrics stores, infrastructure management, and data security.
• Experience building, deploying, and maintaining reliable data pipelines across multiple geographies and at scale.
• Familiarity with workflow or orchestration frameworks such as Airflow and dbt.

Preferred

• Hands-on experience designing data processing patterns for a modern lakehouse architecture.
• Experience designing and developing standard framework modules, high-performance services, and client libraries for big data.
• Experience with technologies such as GCP, Databricks, BigQuery, Dataproc, Kafka, Kubernetes, Spark, Dataflow, Google Cloud Storage, and Airflow.
• Excellent written and verbal communication skills, with the ability to tailor communication for leadership, users, and company-wide audiences.
• Ability to rapidly evaluate technologies and run proofs of concept to inform architecture decisions.
• Experience thriving in a complex environment.

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 know when to align and when to just decide. Collaboration isn’t a way to avoid accountability.
• You’re comfortable operating across time zones with a globally distributed team, including colleagues based in APAC and EMEA.

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 2,300 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 ouroperating principles to see it in full.

About the team

The Knowledge Platform team is at the heart of our company’s data and AI strategy. We are building the foundational infrastructure that empowers the entire company to leverage data, AI, and ML into business impact. We accomplish this by creating platforms that handle the entire data and AI/ML lifecycle, simplifying the interface while providing proper safety and governance. This includes managing our data infrastructure (Databricks, Spark, Kafka, etc.), the technology to serve that data to our users (RAG, MCP, etc.), and the platform to host and govern these AI/ML models.

In 2026, our team’s overarching mission is to evolve our full data ecosystem-encompassing both platform and models-into a fully AI agent-ready infrastructure; we will empower customers to engage directly with the data platform to extract actionable value through capabilities like analytics and natural language querying, while also upgrading the platform to deliver robust, real-time performance for instant, data-driven decision-making.