Engineering Manager - ML/AI (AI Products)

Xero; Sydney; Hybrid; AUD 180.000 - 240.000; Vollzeit

Zusammenfassung

Xero is seeking an Engineering Manager in its Machine Learning & AI team to lead a high-performing group of engineers building AI-powered experiences across Xero.

You will balance delivery with engineering quality, guide architecture, and help scale production ML capabilities while growing your people.

This hybrid role offers Australia-wide flexibility and a path to shape AI-native products at scale.

Qualifikationen

• Experience leading, coaching and developing engineers.
• Ability to translate business goals into executable engineering plans.
• Experience delivering roadmaps in fast-changing environments.

Aufgaben

• Lead a high-performing ML/AI team across AI experiences and backend services.
• Drive MLOps, LLMOps, observability and production reliability.
• Shape technical direction with senior ICs while growing team capabilities.
• Ensure scalable, secure and reliable AI-enabled products for Xero's customers.

Kenntnisse

Leadership

Technical judgment

Roadmap delivery

Hands-on coding

ML/AI knowledge

Jobbeschreibung

The role & impact

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.

• You'll lead engineering across a broad range of technology surfaces, from customer-facing AI experiences and intelligent product workflows to the backend services, platforms and infrastructure that power them. You'll help turn research, models and emerging AI capabilities into reliable, secure and scalable production products that make a real difference for millions of small businesses.

• You'll balance predictable delivery with a relentless focus on engineering quality and system health, building our maturity across MLOps, LLMOps, observability, evaluation and the operational practices needed to run AI systems in production. As AI continues to evolve, you'll also champion AI-native engineering practices and help your team adapt how we design, build, test and operate software.

• Working closely with senior individual contributors, including staff and principal engineers, you'll help shape technical direction while focusing on team growth, delivery excellence and sustainable engineering practices. This is a role for someone who wants to build both the systems and the people that enable Xero to deliver AI-powered products at scale.

The team & how they connect

You'll join Xero's Data & AI organisation, within the AI Products division, reporting to the GM of ML Engineering. The team partners closely with Applied Science, Data Engineering, Product and other engineering teams to bring AI capabilities from research and experimentation into production.
Our scope goes beyond building and serving models. We build the end-to-end engineering capabilities that bring AI to life in Xero's products, spanning traditional ML-powered automation and predictions, conversational AI assistants, LLM-powered workflows and agentic experiences. This means working across the full stack, integrating AI into customer experiences and product workflows while building the front end & backend services, platforms and infrastructure needed to make those experiences safe, reliable and scalable.

It's a collaborative, evolving space where you'll help translate advances in ML and generative AI into practical customer outcomes, while building the engineering foundations to support the next generation of AI-native products.

The team is currently working on

• Production ML and AI engineering: Building and operating the platforms, services and practices that support traditional ML models, generative AI and agentic systems in production.

• JAX (Just Ask Xero): Powering Xero's conversational GenAI assistant and evolving the underlying capabilities to support increasingly sophisticated, context-aware and agentic experiences.

• Intelligent financial workflows: Developing capabilities such as Automated Bank Reconciliation and smart document capture, using ML and AI to match transactions, extract information from bills and receipts, and automate complex tasks.

• XeroForce: Building the platform for AI-powered workflows, enabling agents to plan and execute complex tasks across Xero's products and supporting reliable, reusable agentic experiences at scale.

• End-to-end AI product experiences: Integrating AI into customer-facing experiences and product workflows, alongside the backend services, orchestration and infrastructure that make them work.

Where and how you can work

We support a flexible working model that empowers you to balance your professional and personal life. You'll have the option to work in a hybrid capacity, combining the focus of remote work with the collaboration of our office spaces and team boost days to foster connection and alignment.

Here are some of the things we're looking for, for this role

• You'll bring a strong track record of leading, coaching and developing engineers, building team capability and creating an environment where people can do their best work.

• You have strong technical judgement across architecture, system design and engineering trade-offs, and can guide decisions across a broad and evolving technology landscape.

• You've translated business goals into executable engineering plans, balancing near‑term delivery with long‑term technical health and maintainability.

• You're experienced in delivering roadmaps predictably in fast‑paced, evolving environments, navigating ambiguity and adapting as priorities and technology change.

• You understand what it takes to build and operate production‑grade software, from customer‑facing experiences and backend services through to distributed systems, platforms and infrastructure.

• You stay hands‑on when it counts, comfortable writing, reviewing or debugging production code to unblock your team, support an incident or help resolve a complex technical challenge.

• Experience with machine learning, generative AI or AI‑powered products is a bonus rather than a requirement. You don't need to be an ML specialist, but genuine curiosity about the space and an appetite to learn how these technologies are changing software engineering will help you thrive here.