Engineering Manager - Machine Learning (AI Products) at Xero

Xero; Auckland; Hybrid; NZD 150,000 - 210,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Xero in Auckland is seeking an Engineering Manager to lead a high‑performing ML and platform engineering team. You will turn research and models into production‑grade infrastructure that runs at scale, focusing on system health and reliable delivery.

You will shape the technical architecture with senior ICs, drive MLOps maturity, observability, and AI-native workflows across the software lifecycle, and mentor engineers to grow capabilities while building AI at Xero's scale.

Qualifications

• Proven experience leading engineers and building team capability over time.
• Strong architectural judgement across system design and trade-offs.
• Ability to translate business goals into executable engineering plans.
• Delivery of roadmaps in fast-paced environments.

Responsibilities

• Lead a high-performing ML and platform engineering team.
• Turn research and models into production-grade ML infrastructure at scale.
• Drive MLOps maturity, observability, and production AI reliability.
• Mentor engineers and foster AI-native workflows across the lifecycle.

Skills

Leadership & coaching

System architecture

Delivery planning

Production code review

MLOps awareness

Tools

Kubernetes

CI/CD pipelines

Job description

This Full time on site position offers great opportunities for career growth.

The role & impact

As Engineering Manager, you'll lead a high-performing, inclusive team of ML and platform engineers, responsible for turning research and models into production-grade ML infrastructure that runs at scale. You'll balance predictable delivery with a relentless focus on system health, taking the lead on MLOps maturity, observability and the operational realities of running AI systems in production, not just shipping features. You'll work closely with senior individual contributors, including staff and principal engineers, who shape the technical architecture, while you focus on team growth, delivery rigour and championing AI-native workflows across the software development lifecycle. This is a role for someone who wants to build both the systems and the people capable of running AI at Xero's scale.

The team & how they connect

You will join Xero's Data & AI organisation, within the AI Products division, reporting to the GM of ML Engineering. The team takes research and models from applied scientists and turns them into safe, scalable, production ML infrastructure that millions of small businesses rely on every day. It's a close, cross-functional group that partners tightly with Applied Science, Data Engineering and Product to move ideas from prototype to production. The team is currently working on Production ML infrastructure and MLOps supporting Xero's AI-native product suite Systems powering JAX (Just Ask Xero), Xero's conversational GenAI assistant Auto Bank Rec and smart document capture, including AI-powered transaction matching and extraction from bills and receipts Future work extending cash flow forecasting and other embedded ML capabilities

Where and how you can work

We support a flexible working model that empowers you to balance your professional and personal life. You will 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 bring a strong track record of leading, coaching and developing engineers, with real experience building team capability over time
• Strong technical judgement across architecture, system design and engineering trade-offs is part of how you naturally operate
• You have translated business goals into executable engineering plans, balancing short-term delivery against long-term system health
• Delivering roadmaps predictably in fast-paced, evolving environments is familiar territory for you
• You stay hands-on when it counts, comfortable writing, reviewing or debugging production code to unblock your team or support an incident
• Experience with machine learning or AI systems is a bonus rather than a requirement, though genuine curiosity about the space will help you thrive here