Staff Engineer, Agentic AI
Airwallex is hiring a Staff Engineer, Agentic AI in San Francisco, United States. It pays $182k-$310k a year and Level rates it ; you can apply on Level.
AI in this role
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 our operating principles to see it in full.
How you'll make impactYou’ll design and deploy intelligent systems that automate complex, multi-step financial workflows. You’ll turn agentic frameworks, orchestration layers, and pragmatic model selection into reliable production systems at scale.
Architect intelligent systems that automate complex, multi-step financial workflows
Apply prompting, retrieval-augmented generation, fine-tuning, or training models from scratch as appropriate to the problem
Design and optimize agent architectures for reasoning, tool use, and workflow automation
Build systems that improve with usage and create compounding AI flywheels
Partner with backend and frontend engineers to integrate AI reasoning into secure, production systems
You’ll work from our San Francisco office three days a week.
What we're looking forEssentials
5+ years of experience in applied AI/ML engineering, including production deployments
Strong Python skills and experience with ML frameworks such as PyTorch, JAX, or TensorFlow
A track record of building and deploying AI agents, orchestration frameworks, or multi-step reasoning systems
Experience designing monitoring, evaluation, and iteration practices for production AI systems
Ability to balance innovation with reliability, scalability, and compliance
Experience architecting and deploying intelligent systems that automate complex, multi-step financial workflows
Experience using agentic frameworks, orchestration layers, and pragmatic model selection to build production systems
Experience designing AI systems for reasoning, tool use, and workflow automation
Experience building systems that improve with usage and create compounding AI flywheels
Experience partnering with backend and frontend engineers to integrate AI reasoning into secure, production systems
You're comfortable owning the roadmap yourself.
You're comfortable making decisions with incomplete information and moving quickly anyway.
You hold yourself to a high standard even when no one is watching. Quality and accountability aren't external expectations, they're internal ones.
You're comfortable with ambiguity. Give you a problem, not a prescription, and you'll run with it.
You simplify complexity rather than hiding behind it.
T:0's mission is to make finance run itself. We're building an AI-native accounting platform that closes the books, reconciles, and reports continuously, so founders can stop managing their finances and start using them to run the business. The hard part isn't adding AI to accounting. It's making AI you can trust with the books. We use AI to understand how a business works, then run the actual accounting on strict, checkable rules, and no black box deciding the numbers. That's why customers pick us over both the legacy tools they've outgrown and the AI wrappers they don't trust. And bookkeeping is just the start: we're building toward a full financial operating system for how companies account, plan, and operate. The team is small, elite, and builder-focused, led by operators with a track record of shipping AI products at scale. We sit inside Airwallex, which means startup speed with a scaled company's infrastructure, distribution, and capital behind us. You'll work directly from real customer pain, own outcomes end to end, and ship fast.
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.
How we rate this
Staff Engineer, Agentic AI at Airwallex rates 87 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- What's a project where you used PyTorch hands-on?
- Walk me through how you've used TensorFlow in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, Fine-tuning, PyTorch, and TensorFlow. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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