Software Engineer II, Client Risk

Airwallex2 days ago

Location

SG - Singapore

Type

Full Time

Level

Mid

Role

Backend Engineer

Posted

Mar 12, 2026

Full TimeMid

The role

Summary

Airwallex is seeking a Software Engineer II to join their Client Risk team in Singapore, focusing on building AI-powered risk monitoring systems using machine learning and large language models. The role involves developing scalable distributed systems to detect financial crime and credit risk across Airwallex's global payments platform, serving over 200,000 businesses worldwide.

What you'll do

AI-Powered Risk System Development: Design, build, and maintain cutting-edge risk monitoring systems using AI, ML, and LLM technologies to proactively detect and mitigate client-level financial crime and credit risks

LLM Agent Automation: Develop automated name screening, sanction checking, and anti-money laundering solutions powered by LLM agents, aligned with operational team workflows

Unified Client Management Systems: Build seamless client management systems that consolidate internal and external data into a single source of truth for risk intelligence and decision-making

AI Evaluation Framework Design: Establish robust agent evaluation methodologies and pipelines to objectively measure and demonstrate the effectiveness of AI-driven automation solutions

Scalable Infrastructure Development: Construct and support scalable, highly available, and low-latency distributed systems on public cloud infrastructure (GCP/AWS) with strong data governance

Data Pipeline Engineering: Build and maintain reliable data pipelines, data quality monitoring, and real-time streaming services for risk analytics

Cross-Functional Collaboration: Collaborate with global teams including product, engineering, operations, compliance, and data science to drive impactful risk solutions and operational excellence

What we look for

Technical

Backend Engineering ProficiencySolid backend engineering skills with experience in Java, Python, or Kotlin, preferably with Spring/Spring Boot framework

Distributed Systems ExperienceExperience designing and developing scalable, high-concurrency, high-availability distributed systems in cloud environments

Business Requirements TranslationStrong ability to translate complex business requirements into robust technical solutions, focusing on risk intelligence and automation

Modern Server TechnologiesProficiency with modern server technologies, data modeling, and performance optimization techniques

Outcome-Oriented ApproachClear orientation towards measurable business and customer outcomes with data-driven decision making

Education

Bachelor's DegreeBachelor's degree in Computer Science, Software Engineering, or related technical discipline, or equivalent practical experience

Experience

Communication SkillsExcellent communication and collaboration skills with cross-functional partners, demonstrating proactive, pragmatic, and driven approach

Fintech Domain Knowledge (Preferred)Experience in or knowledge of financial crime, risk management, compliance, or fintech domains

LLM Agent Experience (Preferred)Proven experience with LLM agent frameworks, RAG pipelines, langchain, langfuse, or MCP

Production AI Implementation (Preferred)Experience implementing production-grade AI/LLM-driven workflow automation for operational review processes

Machine Learning Experience (Preferred)Hands-on machine learning experience for predictive risk analytics, fraud detection, or operational automation

Big Data Technologies (Preferred)Familiarity with real-time data streaming (Kafka/Flink) and big data technologies (Spark, BigQuery, Airflow, ElasticSearch)

Skills

Required skills

Java/Python/KotlinBackend development proficiency in at least one of these languages with Spring framework preference

Distributed SystemsDesign and development of scalable, high-availability systems in cloud environments

Cloud PlatformsExperience with GCP or AWS for building scalable infrastructure solutions

System ArchitectureAbility to design robust technical solutions from complex business requirements

Performance OptimizationModern server technologies, data modeling, and system performance tuning

Nice to have

Financial Crime/Risk ManagementDomain knowledge in financial crime, compliance, or risk management within fintech

LLM Agent FrameworksExperience with RAG pipelines, LangChain, LangFuse, or Model Context Protocol (MCP)

Machine LearningHands-on ML experience for predictive analytics, fraud detection, or automation

Real-time Data StreamingApache Kafka, Flink, and other streaming technologies for real-time processing

Big Data TechnologiesSpark, BigQuery, Airflow, ElasticSearch for large-scale data processing

AI Evaluation FrameworksExperience designing evaluation methodologies for AI-driven automation solutions

Compensation & benefits

Benefits

Global Career Growth

Opportunity to work with over 2,000 innovative professionals across 26 offices globally in a fast-growing fintech valued at US$8 billion

High-Impact Work Environment

Tackle complex, high-visibility problems with exceptional teammates while building the future of global banking and payments

AI-First Innovation

Work with cutting-edge AI technologies including machine learning, large language models, and agent frameworks in production environments

Equal Opportunity Employment

Work in an inclusive environment that values diversity and provides equal opportunities regardless of background or identity

Accommodation Support

Disability and special need accommodations provided to ensure an inclusive workplace for all employees

Interview process

1
Application Review — Initial screening of resume and application materials focusing on technical background and relevant experience in distributed systems and AI/ML
2
Technical Phone Screen — Technical discussion covering backend engineering concepts, system design principles, and experience with risk management or fintech domains
3
System Design Interview — Design scalable risk monitoring systems, discussing trade-offs in distributed architectures, cloud platforms, and real-time data processing
4
AI/ML Technical Round — Deep dive into machine learning concepts, LLM agent frameworks, and practical experience with AI-driven automation in production environments
5
Behavioral Interview — Assessment of collaboration skills, cross-functional partnership experience, and alignment with Airwallex's mission and operating principles
6
Final Round — Meet with team members and leadership to discuss role expectations, team dynamics, and mutual fit for the Client Risk team