AI Engineer
Mid · Full Time
Opens Airwallex's application page
Role
What you'll do.
Airwallex is seeking an AI Engineer to join their elite team building production AI systems that automate financial workflows for startups globally. The role involves architecting and deploying AI agents using cutting-edge frameworks like LangChain, AutoGen, and CrewAI, while applying techniques from prompt engineering to fine-tuning models. You'll work on high-impact problems with direct customer impact in a fast-paced fintech environment.
Responsibilities
- AI Agent Architecture: Architect and deploy AI agents using frameworks like LangChain, LlamaIndex, AutoGen, CrewAI, and Semantic Kernel
- Model Selection and Optimization: Apply appropriate AI techniques across the spectrum from prompting and RAG to fine-tuning and training from scratch
- System Design: Design and optimize agent architectures for reasoning, tool use, and workflow automation
- Self-Improving Systems: Build systems that improve with usage, creating compounding AI flywheels for enhanced performance
- Cross-functional Integration: Collaborate with backend and frontend engineers to integrate AI reasoning into secure, production systems
- Production Deployment: Deploy intelligent systems that automate complex, multi-step financial workflows
- Customer-Centric Development: Work backward from real founder pain points to deliver meaningful automation solutions
Qualifications
What we look for.
Technical
AI/ML Engineering
2+ years of applied AI/ML engineering experience with production deployments
Python Proficiency
Strong Python programming skills for ML/AI development
ML Frameworks
Experience with machine learning frameworks including PyTorch, JAX, and TensorFlow
Agent Systems
Track record of building and deploying AI agents, orchestration frameworks, or multi-step reasoning systems
Production Systems
Understanding of monitoring, evaluation, and iteration in production AI systems
System Reliability
Ability to balance innovation with reliability, scalability, and compliance requirements
Education
Degree Preference
Bachelor's or Master's degree in Computer Science, AI/ML, or related technical field preferred
Experience
Production AI
2+ years of hands-on experience building and deploying AI systems in production environments
Agent Frameworks
Demonstrated experience with AI agent frameworks and orchestration systems
Fintech Experience
Previous experience in financial technology or automated workflow systems is highly valued
Skills
Required
Python Programming
Advanced proficiency in Python for AI/ML development and production systems
AI Agent Frameworks
Hands-on experience with LangChain, AutoGen, CrewAI, or similar orchestration frameworks
Machine Learning
Deep understanding of ML concepts, model training, and deployment strategies
Production Systems
Experience building scalable, reliable AI systems for production environments
System Architecture
Ability to design complex AI workflows and multi-agent systems
Preferred
Fintech Domain
Nice to haveUnderstanding of financial services, payments, or automated workflow challenges
RAG Systems
Nice to haveExperience with Retrieval-Augmented Generation and knowledge-base integration
Model Fine-tuning
Nice to haveExperience with custom model optimization and domain-specific training
Cloud Platforms
Nice to haveFamiliarity with AWS, GCP, or Azure for ML model deployment and scaling
API Integration
Nice to haveExperience integrating AI systems with external APIs and financial services
Tech stack
Languages
Frameworks
Tools
Other
Compensation
Pay and benefits.
Base·USD 120,000 – 200,000
Equity·Stock options
Benefits
Equity Package
Competitive equity participation in a fast-growing fintech unicorn valued at $8 billion
Health Insurance
Comprehensive medical, dental, and vision coverage for employees and dependents
Professional Development
Learning and development budget for conferences, courses, and skill enhancement
Flexible Work
Hybrid work arrangement with flexibility between office and remote work
Global Exposure
Opportunity to work with international teams across 26 global offices
Innovation Time
Dedicated time for exploring new AI technologies and experimental projects
Process
Interview steps.
- 01
Initial Screening
Phone or video call with talent acquisition to discuss background and role fit
- 02
Technical Assessment
AI/ML focused coding challenge or take-home project demonstrating agent system design
- 03
Technical Interview
Deep-dive technical discussion on AI frameworks, model selection, and system architecture
- 04
System Design
Design session focused on building scalable AI agent systems for financial automation
- 05
Team Interview
Meet with AI team members to discuss collaboration, problem-solving approach, and cultural fit
- 06
Final Interview
Leadership interview covering career goals, impact expectations, and role-specific scenarios
Full posting
Original listing.
About Airwallex
Airwallex is the only unified payments and financial platform for global businesses. Powered by our unique combination of proprietary infrastructure and software, we empower over 200,000 businesses worldwide – including Brex, Rippling, Navan, Qantas, SHEIN and many more – with fully integrated solutions to manage everything from business accounts, payments, spend management and treasury, to embedded finance at a global scale.
Proudly founded in Melbourne, we have a team of over 2,000 of the brightest and most innovative people in tech across 26 offices around the globe. Valued at US$8 billion and backed by world-leading investors including T. Rowe Price, Visa, Mastercard, Robinhood Ventures, Sequoia, Salesforce Ventures, DST Global, and Lone Pine Capital, Airwallex is leading the charge in building the global payments and financial platform of the future. If you’re ready to do the most ambitious work of your career, join us.
Attributes We Value
We hire successful builders with founder-like energy who want real impact, accelerated learning, and true ownership. You bring strong role-related expertise and sharp thinking, and you’re motivated by our mission and operating principles. You move fast with good judgment, dig deep with curiosity, and make decisions from first principles, balancing speed and rigor.
You're humble and collaborative; turn zero‑to‑one ideas into real products, and you “get stuff done” end-to-end. You use AI to work smarter and solve problems faster. Here, you’ll tackle complex, high‑visibility problems with exceptional teammates and grow your career as we build the future of global banking. If that sounds like you, let’s build what’s next.
About the Team
This team is building production AI that eliminates financial busywork for startups globally. We're delivering intelligent automation across payments, payroll, bookkeeping, and tax—freeing founders to focus on building their companies instead of managing finances.
We leverage cutting-edge AI tooling across the spectrum: from prompt engineering and in-context learning to fine-tuned models and agentic systems, choosing the right approach for each problem. We work backward from real founder pain points, own customer outcomes, and ship fast.
The team is small, elite, and builder-focused, led by operators with a track record of shipping AI products at scale. You'll solve hard technical problems with real autonomy and direct customer impact.
About the Role
You’ll be a core builder in our AI team, designing and deploying intelligent systems that automate complex, multi-step workflows. You’ll leverage agentic frameworks, advanced orchestration, and pragmatic model selection to take ideas from whiteboard to production.
What You’ll Do
Architect and deploy AI agents using frameworks like LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, and emerging OSS stacks.
Apply the right techniques across the AI spectrum — prompting, RAG, fine-tuning, or training from scratch.
Design and optimize agent architectures for reasoning, tool use, and workflow automation.
Build systems that improve with usage, creating compounding AI flywheels.
Work with backend and frontend engineers to integrate AI reasoning into secure, production systems.
What You Need to Have
2+ years in applied AI/ML engineering with production deployments.
Strong Python skills and experience with ML frameworks (PyTorch, JAX, TensorFlow).
Track record of building and deploying AI agents, orchestration frameworks, or multi-step reasoning systems.
Understanding of monitoring, evaluation, and iteration in production AI systems.
Ability to balance innovation with reliability, scalability, and compliance.
Applicant Safety Policy: Fraud and Third-Party Recruiters
To protect you from recruitment scams, please be aware that Airwallex will not ask for bank details, sensitive ID numbers (i.e. passport), or any form of payment during the application or interview process. All official communication will come from an @airwallex.com email address. Please apply only through careers.airwallex.com or our official LinkedIn page.
Airwallex does not accept unsolicited resumes from search firms/recruiters. Airwallex will not pay any fees to search firms/recruiters if a candidate is submitted by a search firm/recruiter unless an agreement has been entered into with respect to specific open position(s). Search firms/recruiters submitting resumes to Airwallex on an unsolicited basis shall be deemed to accept this condition, regardless of any other provision to the contrary.
Equal opportunity
Airwallex is proud to be an equal opportunity employer. We value diversity and anyone seeking employment at Airwallex is considered based on merit, qualifications, competence and talent. We don’t regard color, religion, race, national origin, sexual orientation, ancestry, citizenship, sex, marital or family status, disability, gender, or any other legally protected status when making our hiring decisions. If you have a disability or special need that requires accommodation, please let us know.
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