Engineering Manager - Machine Learning (AI Products)

Role and Impact

As an Engineering Manager, you will lead a highly skilled and inclusive team of machine learning and platform engineers dedicated to transforming research and models into robust, production-level ML infrastructure that scales efficiently. Your role involves balancing consistent project delivery with a strong emphasis on the reliability and operational management of AI systems, including improving MLOps maturity and system observability beyond merely shipping new features.

Team Collaboration

You will collaborate closely with senior engineers, including staff and principal engineers, who influence the technical architecture. Your focus will be on nurturing team growth, enforcing rigorous delivery standards, and promoting AI-centric workflows throughout the software development lifecycle. This position offers the opportunity to develop both sophisticated systems and skilled teams that operate AI solutions at scale.

About the Team

You will be part of Xero's Data & AI organization within the AI Products division, reporting directly to the General Manager of ML Engineering. This cross-functional team works with applied scientists and data engineers, turning prototypes and research models into dependable production ML platforms that support millions of small businesses daily. The group partners with Applied Science, Data Engineering, and Product departments to move innovation into production seamlessly.

Current Projects

• Developing production ML infrastructure and MLOps solutions that support Xero's AI-native product line.
• Building systems for JAX (Just Ask Xero), the conversational generative AI assistant.
• Enhancing features like Auto Bank Rec and smart document capture, including AI-driven transaction matching and extraction from bills and receipts.
• Planning future initiatives such as cash flow forecasting and other embedded ML functions.

Work Environment

The company supports a flexible work structure to help you balance your professional and personal commitments. You can work remotely or adopt a hybrid model that mixes remote work with in-office collaboration days designed to strengthen team connections and alignment.

Candidate Profile

• Proven leadership in developing engineering teams with experience in coaching and expanding team capabilities.
• Strong technical acumen in system architecture, design, and making engineering trade-offs.
• Ability to translate business objectives into actionable engineering plans that maintain balance between immediate delivery and long-term system sustainability.
• Experience managing project roadmaps and delivering results predictably in dynamic environments.
• Capability and willingness to engage hands-on in code writing, reviewing, or debugging to support the team or resolve incidents.
• While direct experience with machine learning or AI systems is advantageous, curiosity and interest in this domain are welcomed and considered valuable.

Inclusivity Statement

The company embraces diverse backgrounds and skills and encourages applications even if your experience isn't a perfect match. Hiring decisions emphasize skills, passion, and the unique perspectives candidates bring to enhance the culture and team dynamics.