Top AI & Machine Learning Jobs

Lead and grow Xero’s Internal AI Accelerator engineering team, owning the strategy, delivery, and roadmap for production agentic AI workflows. Build reusable AI patterns, platforms, governance frameworks, and enterprise architectures across finance, HR, support, and operations. Establish practices for AI safety, evaluation, and scalable operations while coaching engineers, partnering with senior stakeholders, and translating business needs into deliverable technical solutions.

Develop and evolve data, privacy, and AI governance frameworks; translate regulatory and policy requirements into practical guidance; establish stewardship models, governance forums, and supporting tooling; deliver data and AI literacy programs; and advise cross-functional teams on responsible AI, bias, transparency, explainability, data quality, lineage, and regulatory compliance.

Lead data and AI governance across Xero by evolving governance frameworks, translating policies into practical guidance, delivering data and AI literacy programs, and partnering with technical, privacy, regulatory, security, and risk teams. The role focuses on responsible AI adoption, data stewardship, quality, lineage, transparency, bias, explainability, and regulatory readiness.

Develop and improve data and AI governance frameworks, translate policies into practical guidance, deliver data and AI literacy programs, and advise cross-functional teams on responsible AI, privacy, risk, transparency, bias, and regulatory compliance. The role partners with Product, Security, Privacy, Regulatory, Risk, and engineering teams to implement governance across Xero.

Build and operate AI enablement platforms, internal skills marketplaces, and AI tool distribution systems used by engineering teams. Develop agent skills and remediation agents, establish AI engineering best practices, and manage production reliability through monitoring, runbooks, and rollback planning. Collaborate with AWS, Microsoft, and GitHub on early-access technologies while influencing technical direction and supporting a growing AI-focused team.

Manages a distributed team of three data scientists while personally leading North American marketing measurement. Responsibilities include campaign and event measurement, churn analysis, funnel effectiveness, AI-driven insight generation, and agentic analytics. The role requires translating complex analysis into actionable recommendations, partnering with marketing teams, coaching across time zones, and establishing sustainable delivery practices.

Leads Xero’s global data science, analytics, ML, and AI strategy across multiple product areas. The role manages and scales a multidisciplinary organization, advises executive leadership, oversees AI governance, model risk, data quality, privacy, experimentation, and enterprise data architecture, and drives AI-powered products including chatbots and agentic workflows. It also establishes operating models, develops leaders, manages strategic risks, and partners cross-functionally to deliver company-wide data and AI impact.

Design, build, and operate an internal AI skills marketplace and distribution platform. Own end-to-end delivery from experimentation to production, create runbooks, monitoring, rollback plans, and provide guidance on authoring agent skills while collaborating with vendors and engineering teams.

Build and rapidly deploy internal AI-powered tools and automations that reduce operational toil. Integrate Jira, Confluence, Workday, and data warehouses through APIs; automate reporting, headcount management, and roadmapping workflows; evaluate custom, low-code, and SaaS solutions; prototype scalable AI-enabled improvements; and mentor operations teams in modern AI tooling.

Lead the design, delivery, and operation of agentic AI workflows and applications from discovery through production. Partner with business teams to automate complex workflows, integrate AI with enterprise platforms, and establish reusable patterns, guardrails, evaluation frameworks, and monitoring. Collaborate with product owners and subject-matter experts, translate business needs into technical solutions, and coach teams to improve AI fluency and adoption.