Engineering Manager — AI/ML Production Systems (Hybrid)

Xero; Auckland; Hybrid; NZD 180,000 - 240,000; Full time

Job summary

Xero is seeking an Engineering Manager to lead a high-performing team of ML and platform engineers, turning research into production-grade ML infrastructure at scale. You’ll balance delivery with system health, drive MLOps maturity and observability, and champion AI-native workflows across the full software lifecycle.

You’ll work with staff and principal engineers to shape architecture while focusing on team growth and delivery discipline, ensuring we run AI at Xero’s scale with rigor and care.

Qualifications

• You’ll 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.
• You’ve 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.

Responsibilities

• Lead, coach and develop ML and platform engineers to scale production ML infrastructure.
• Drive MLOps maturity, observability and reliability of AI systems in production.
• Collaborate with senior ICs to shape technical architecture while focusing on team growth.
• Translate research into production-ready ML systems at Xero’s scale.

Skills

Team leadership

System architecture

MLOps

Production code

Roadmapping

Cross-functional collaboration

Hands-on coding

Job description

Xero is seeking an Engineering Manager to lead a high-performing team of ML and platform engineers, turning research into production-grade ML infrastructure at scale. You’ll balance delivery with system health, drive MLOps maturity and observability, and champion AI-native workflows across the full software lifecycle.

You’ll work with staff and principal engineers to shape architecture while focusing on team growth and delivery discipline, ensuring we run AI at Xero’s scale with rigor and care.