Xero
Senior Software Engineer - ML & AI (AI Products)
AU: Sydney (45 Clarence St), Remote. Posted 12 days ago
The role
You will design, build and own the production systems behind Xero's AI features. This includes the services, pipelines and infrastructure that power LLM-driven and agentic experiences.
What you will do
- Design, build and own production systems behind AI features
- Build and operate services, pipelines and infrastructure for LLM-driven and agentic experiences
- Make architecture decisions regarding scale, cost, reliability and shipping speed
- Set engineering standards
- Mentor engineers
- Partner across Xero to make data usable and systems dependable
- Partner with Applied Scientists to build interfaces and harnesses for production models
- Own engineering and infrastructure of ML and AI systems including reliability, cost and scale
Required qualifications
- Track record of designing, shipping and operating production-grade backend systems at scale
- Experience building and operating production systems for LLM or agentic workloads (orchestration, tool use, evaluation, guardrails, latency and cost management)
- Strong system design fundamentals
- Excellent coding in Python, or another language suited to web-scale services (Go, Java, Kotlin, TypeScript)
- Experience with APIs and service design, cloud infrastructure (ideally AWS), CI/CD and observability
- Experience running services in production, including on-call and incident response
- Solid SQL
- Experience with large-scale data processing
- Excellent communication to explain complex technical concepts to business and technical audiences
- A coaching mindset and the ability to set engineering standards and mentor other engineers
Nice to have
- Experience operationalizing ML or LLM workloads (inference serving, evaluation pipelines)
- Familiarity with MLflow, PyTorch or TensorFlow, and data orchestration tools
- Distributed processing experience (Spark, Dask)
About the company
Xero is a company with a globally distributed team of scientists, engineers, product managers and analysts within their Data & AI business.