Engineering Manager - ML & AI Systems (AI Products)

As an Engineering Manager in our Machine Learning & AI team, you'll lead a high-performing, inclusive team of engineers building and operating AI-powered experiences and capabilities across Xero. The team's work spans traditional machine learning, from predictive models and intelligent automation through to LLM-powered and agentic AI experiences that bring new ways for customers to interact with and get value from Xero.

Responsibilities

Lead engineering across customer-facing AI experiences, intelligent product workflows, backend services, platforms and infrastructure; Turn research, models and emerging AI capabilities into reliable, secure and scalable production products; Balance predictable delivery with engineering quality and system health; Build maturity across MLOps, LLMOps, observability, evaluation and operational practices for AI systems in production; Champion AI-native engineering practices; Lead, coach and develop a high-performing, inclusive team of engineers; Work with senior individual contributors, including staff and principal engineers, to shape technical direction

Requirements

Strong track record of leading, coaching and developing engineers, building team capability and creating an environment where people can do their best work; Strong technical judgement across architecture, system design and engineering trade-offs; Experience translating business goals into executable engineering plans, balancing near-term delivery with long-term technical health and maintainability; Experience delivering roadmaps predictably in fast-paced, evolving environments, navigating ambiguity and adapting as priorities and technology change; Understanding of building and operating production-grade software, from customer-facing experiences and backend services through to distributed systems, platforms and infrastructure; Stays hands-on, comfortable writing, reviewing or debugging production code to unblock the team, support an incident or resolve complex technical challenges

Nice to have

Experience with machine learning, generative AI or AI-powered products; Genuine curiosity about AI and an appetite to learn how these technologies are changing software engineering

Benefits

Flexible working model; Hybrid working combining remote work with office collaboration and team boost days