AI Engineer

Airwallex1 weeks ago

Location

US - San Francisco

Type

Full Time

Salary

USD 120,000 – 200,000

Level

Mid

Role

AI Engineer

Posted

Mar 7, 2026

Full TimeMid

The role

Summary

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.

What you'll do

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

What we look for

Technical

AI/ML Engineering2+ years of applied AI/ML engineering experience with production deployments

Python ProficiencyStrong Python programming skills for ML/AI development

ML FrameworksExperience with machine learning frameworks including PyTorch, JAX, and TensorFlow

Agent SystemsTrack record of building and deploying AI agents, orchestration frameworks, or multi-step reasoning systems

Production SystemsUnderstanding of monitoring, evaluation, and iteration in production AI systems

System ReliabilityAbility to balance innovation with reliability, scalability, and compliance requirements

Education

Degree PreferenceBachelor's or Master's degree in Computer Science, AI/ML, or related technical field preferred

Experience

Production AI2+ years of hands-on experience building and deploying AI systems in production environments

Agent FrameworksDemonstrated experience with AI agent frameworks and orchestration systems

Fintech ExperiencePrevious experience in financial technology or automated workflow systems is highly valued

Skills

Required skills

Python ProgrammingAdvanced proficiency in Python for AI/ML development and production systems

AI Agent FrameworksHands-on experience with LangChain, AutoGen, CrewAI, or similar orchestration frameworks

Machine LearningDeep understanding of ML concepts, model training, and deployment strategies

Production SystemsExperience building scalable, reliable AI systems for production environments

System ArchitectureAbility to design complex AI workflows and multi-agent systems

Nice to have

Fintech DomainUnderstanding of financial services, payments, or automated workflow challenges

RAG SystemsExperience with Retrieval-Augmented Generation and knowledge-base integration

Model Fine-tuningExperience with custom model optimization and domain-specific training

Cloud PlatformsFamiliarity with AWS, GCP, or Azure for ML model deployment and scaling

API IntegrationExperience integrating AI systems with external APIs and financial services

Compensation & benefits

Salary

USD 120,000 – 200,000 (annual)

Stock options

Available

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

Interview process

1
Initial Screening — Phone or video call with talent acquisition to discuss background and role fit
2
Technical Assessment — AI/ML focused coding challenge or take-home project demonstrating agent system design
3
Technical Interview — Deep-dive technical discussion on AI frameworks, model selection, and system architecture
4
System Design — Design session focused on building scalable AI agent systems for financial automation
5
Team Interview — Meet with AI team members to discuss collaboration, problem-solving approach, and cultural fit
6
Final Interview — Leadership interview covering career goals, impact expectations, and role-specific scenarios