Senior Backend Engineer, Agentic AI

About the role

Airwallex, the AI-native financial operating system used by more than 675,000 businesses, is hiring a Senior Backend Engineer for its T:0 team, which is building an AI-native accounting platform. You will help design the backend foundations of intelligent finance systems: scalable services, resilient APIs and data models that support agentic workflows, AI copilots and real-time financial infrastructure. You will work from the San Francisco office three days a week.

Key responsibilities

• Build typed, production-grade APIs and services in Python using FastAPI and Pydantic.
• Develop resilient infrastructure primitives such as queues, retries, idempotency, observability and backpressure handling.
• Work at the intersection of systems and AI, building feedback loops where product data continuously improves models and models improve system behaviour.
• Ship platform foundations including internal frameworks, SDKs and tooling that accelerate engineers across the organisation.
• Partner with ML and product teams to turn research-grade ideas into customer-facing systems.
• Help define the architecture of an AI-native financial stack, designing software with AI as a first-class runtime.

Required profile

• 5+ years of backend engineering experience with Python at scale.
• Deep knowledge of SQL and NoSQL database design.
• Experience with distributed systems, event-driven architectures or microservices.
• Strong understanding of security and compliance best practices.
• Experience designing and operating reliable, production-grade services.
• Comfortable owning the roadmap, making decisions with incomplete information and working with ambiguity.

Required skills

• Python, FastAPI and Pydantic
• SQL and NoSQL databases
• GCP services such as Pub/Sub, Cloud Run, Cloud SQL, BigQuery and KMS
• Distributed systems, event-driven architectures or microservices

Preferred: experience with agentic workflows, AI copilots or AI-native products; experience with financial systems, ledgers, payments or accounting; experience building internal platforms, frameworks, SDKs or developer tooling; experience partnering with ML and product teams.