Senior AI Systems Engineer - Production ML & LLM

K1 Industries; Melbourne; Híbrido; AUD 140.000 - 190.000; Jornada completa

Descripción de la vacante

Xero is seeking a production-focused Software Engineer to design, build and own the production systems behind our AI features. You will shape the services, pipelines and infrastructure powering LLM-driven experiences at scale.

You don't need a machine learning background; we value strong engineers who can operate systems, with optional ML depth learned on the team. Hybrid work, strong collaboration, and reliable delivery are core expectations.

Formación

• Design, build, and operate production-grade backend systems at scale.
• Experience with LLM or agentic workloads and related orchestration/evaluation/guardrails.
• Proficient in Python (or similar web-scale languages) and modern cloud architectures.
• Experience with APIs, service design, cloud infra (AWS), CI/CD, and observability.
• Experience running services in production, on-call and incident response.

Responsabilidades

• Design, build and own production systems powering AI features.
• Define standards and mentor engineers to raise engineering capabilities across AI products.
• Collaborate with cross-functional teams to deliver reliable, scalable ML/AI experiences.
• Own the reliability, cost, latency, and scalability of ML/AI systems deployed to production.
• Contribute to end-to-end AI product experiences and integration with backend services.

Conocimientos

Backend systems

LLM workloads

Python

Cloud / AWS

CI/CD

On-call/Incident response

SQL / Data processing

Communication

Coaching/Mentoring

Herramientas

AWS

CI/CD tools

Observability tools

Descripción del empleo

Xero is seeking a production-focused Software Engineer to design, build and own the production systems behind our AI features. You will shape the services, pipelines and infrastructure powering LLM-driven experiences at scale.

You don't need a machine learning background; we value strong engineers who can operate systems, with optional ML depth learned on the team. Hybrid work, strong collaboration, and reliable delivery are core expectations.