Engineering Manager - AI Workflows
Engineering Manager · Manager · Full Time
Opens Xero's application page
Role
What you'll do.
Lead and grow Xero's Internal AI Accelerator team, scaling agentic AI workflows across business domains while building reusable patterns and governance frameworks. This Engineering Manager role requires solid production engineering credibility, pragmatic strategic thinking, and the ability to bridge technical and business stakeholders to deliver enterprise AI deployments at scale across finance, HR, support, and operations functions.
Responsibilities
- Lead and Grow the Internal AI Accelerator Team: Scale the engineering squad from its current proof-of-concept phase into a fully formed, high-impact team. Recruit, mentor, and develop engineers who will drive agentic AI delivery across Xero's business units. Establish team culture, processes, and technical standards that enable rapid iteration and learning from every project.
- Own Strategy and Roadmap for AI Workflows: Define and execute the strategic vision for how Xero designs and delivers agentic AI workflows that eliminate manual toil and generate measurable productivity gains. Translate business objectives into clear engineering priorities and technical direction, pivoting as market conditions and stakeholder needs evolve.
- Build Reusable AI Patterns and Governance Frameworks: Design and document reusable patterns, platforms, and governance frameworks that enable other teams across Xero to adopt and scale AI delivery independently. Create reference architectures and playbooks that outlive your tenure, establishing lasting best practices for enterprise AI deployments.
- Partner Directly with Business Leaders: Collaborate closely with senior stakeholders and business leaders across General & Administrative, Finance, Procurement & Compliance, and IT functions to co-build AI solutions that address real operational pain points. Embed your team within business units to understand domain-specific challenges and design fit-for-purpose workflows.
- Establish AI Safety and Operations at Scale: Implement technical architectures and operational procedures that ensure enterprise AI deployments are safe, evaluated rigorously, and maintainable at scale. Define evaluation metrics, monitoring practices, and governance controls that give stakeholders confidence in agentic AI systems.
- Drive Delivery and Unblock Technical Execution: Set the pace for shipping, remove blockers for your engineering team, and maintain accountability to production releases that real users depend on. Balance strategic planning with tactical execution, ensuring the team ships outcomes not just code, with measurable impact on productivity and business outcomes.
- Bridge Technical and Business Communication: Translate between engineering technical depth and business strategic intent, ensuring alignment without losing nuance on either side. Present complex AI architecture and operational challenges to non-technical stakeholders in actionable terms while maintaining technical rigor with your engineering team.
Qualifications
What we look for.
Technical
Production Software Architecture and Scale
Demonstrated experience shipping production software at scale, with deep understanding of distributed systems, system design, and the engineering practices required to maintain reliability and performance in enterprise environments.
Agentic AI Systems and Large Language Models
Strong foundational knowledge of agentic AI architectures, large language models (LLMs), prompt engineering, and the operational challenges of deploying AI agents in production. Understanding of AI safety considerations, evaluation methodologies, and governance patterns.
Cloud Platforms and Infrastructure
Experience with cloud-native technologies, containerization, orchestration, and the infrastructure required to support scalable AI workloads. Familiarity with platforms like AWS, Azure, or GCP and their AI/ML services.
Backend and Full-Stack Development
Solid technical foundation in backend engineering, APIs, and full-stack systems architecture. Ability to evaluate technical trade-offs, review code and designs, and make sound architecture decisions without requiring day-to-day coding.
Education
Bachelor's Degree in Computer Science or Related Field
Formal education in Computer Science, Software Engineering, Information Technology, or equivalent technical discipline. Alternatively, equivalent professional experience and demonstrated technical mastery through portfolio, open-source contributions, or technical depth.
Experience
Engineering Management Leadership
Proven track record managing engineering teams, with experience growing headcount, establishing technical culture, coaching engineers toward impact, and delivering measurable business outcomes. Experience managing 4-12 engineers is ideal.
Cross-Functional Collaboration at Scale
Demonstrated ability working across multiple business units, product teams, and stakeholders simultaneously. Experience translating business objectives into technical roadmaps and embedding engineering teams within business organizations.
AI/ML Products or Infrastructure
Experience shipping AI or ML products, platforms, or internal tools that delivered measurable value. Exposure to the unique operational and governance challenges of enterprise AI systems at scale.
Strategic Product and Technical Leadership
Track record of setting technology strategy, building reusable platforms or frameworks that enable other teams, and establishing engineering playbooks that scale beyond your immediate team.
Skills
Required
Engineering Leadership and Team Development
Ability to recruit, mentor, coach, and retain high-performing engineers. Experience setting technical direction, establishing team culture, and creating psychological safety for innovation and learning.
Agentic AI Architecture and LLM Operations
Understanding of agentic AI design patterns, orchestration frameworks, LLM fine-tuning, prompt engineering, and the operational practices required to run AI agents reliably in production.
Strategic Thinking and Pragmatic Execution
Ability to move fast with incomplete information, transform vague problems into clear scope, adapt strategy based on learnings, and balance long-term vision with short-term delivery without perfectionism.
Stakeholder Communication and Translation
Skill in translating technical complexity for business audiences while maintaining technical rigor with engineering teams. Ability to align diverse stakeholders around shared objectives and navigate competing priorities.
Systems Thinking and Technical Architecture
Strong mental models for distributed systems, API design, data architecture, and enterprise software patterns. Ability to evaluate technical trade-offs and make sound architecture decisions across multiple domains.
Preferred
Startup or High-Growth Environment Experience
Nice to haveExperience scaling teams and technical infrastructure in fast-growing companies where speed, adaptability, and scrappiness are valued alongside engineering excellence.
Open-Source Contribution or Community Leadership
Nice to haveActive involvement in open-source projects, technical writing, conference speaking, or community building that demonstrates thought leadership in AI, systems design, or engineering management.
Enterprise SaaS and B2B Domain Knowledge
Nice to haveFamiliarity with enterprise software requirements, regulatory compliance considerations, multi-tenant architecture, and the unique governance and operational practices required in SaaS platforms.
Financial Services or Business Operations Domain
Nice to haveDomain knowledge in accounting, finance, payroll, or business operations. Understanding of the workflows and pain points that Xero's customers experience.
DevOps, Infrastructure, and Operational Excellence
Nice to haveExperience with infrastructure-as-code, CI/CD pipelines, observability and monitoring, and the operational practices that enable reliable, maintainable production systems at scale.
Tech stack
Languages
Frameworks
Databases
Tools
Other
Compensation
Pay and benefits.
Base·AUD 160,000 – 220,000
Equity·Stock options
Benefits
Hybrid Flexible Work Arrangement
Work from Sydney with hybrid flexibility. Core collaboration days in office with regular boost days bringing ANZ teams together for connection and planning. Xero supports diverse ways of working tailored to team needs and individual circumstances.
Professional Development and Learning Budget
Investment in your growth through training, conferences, and educational opportunities. Access to resources for staying current with AI, systems design, and engineering leadership best practices.
Competitive Superannuation and Benefits
Comprehensive superannuation package, health insurance, and standard employee benefits aligned with Australian employment standards and Xero's values.
Equity Participation
Opportunity to participate in Xero's equity or long-term incentive programs, aligning your success with the company's growth and enabling wealth building.
Collaborative and Innovative Culture
Work in a high-impact environment with genuine curiosity about what works and what doesn't. Collaborate with talented engineers and business leaders who value learning and bold thinking.
Direct Influence on Company Strategy
Shape how Xero thinks about AI delivery and enterprise architecture. Your decisions on patterns, frameworks, and governance will influence the company's AI strategy long-term.
Process
Interview steps.
- 01
Recruiter Screening Call (30 minutes)
Initial conversation with Xero's recruitment partner to discuss your background, motivation for the role, and alignment with the Engineering Manager expectations. Come prepared to discuss your most significant impact leading teams and shipping AI/ML products.
- 02
Hiring Manager Conversation (45 minutes)
Deep-dive discussion with the VP of Engineering or equivalent hiring manager. Focus on your strategic thinking, approach to team development, experience scaling AI systems, and how you navigate ambiguity. Bring examples of how you've built reusable frameworks or patterns that enabled other teams.
- 03
Technical Leadership Panel (60 minutes)
Conversation with 2-3 senior engineers or architects to assess your technical depth in agentic AI systems, distributed systems, and enterprise architecture. Discuss a complex technical challenge you've solved, your decision-making framework, and how you stay technically credible without coding full-time.
- 04
Business Leadership Round (45 minutes)
Conversation with stakeholders from business units (Finance, HR, or Operations) who partner with the AI team. Assess your ability to translate business problems into technical roadmaps and your comfort embedding with non-technical stakeholders. Come prepared to discuss how you've bridged technical and business worlds.
- 05
Culture and Values Conversation (30 minutes)
Chat with a peer-level or senior leader to discuss Xero's 'Go Bold' leadership philosophy, your approach to coaching and development, and how you create psychological safety for innovation. Discuss how you balance speed with quality and handle disagreement.
- 06
Offer and Negotiation
Successful candidates will receive a comprehensive offer including base salary, equity, superannuation, and benefits. Xero typically provides 3-5 business days to review and negotiate before a final decision.
Full posting
Original listing.
Engineering Manager - Applied AI
The role and its impact
You will lead and grow the Internal AI Accelerator team as it expands from its current core to a fully formed engineering squad. You will own the strategy, delivery, and roadmap for how Xero designs and delivers agentic AI workflows that eliminate manual toil, speed up decision-making, and generate measurable productivity gains. This means working directly with business leaders across G&A, Finance, P&C, and IT functions to co-build reusable AI patterns and governance frameworks that last. You will shape how Xero thinks about AI delivery long after your tenure, building playbooks and reference architectures that other teams can pick up and run with.
What your engineers build goes into production and real people rely on it. One month you are partnering with finance, the next you are embedded in IT. You set the pace, you unblock the path, and you hold your team accountable to shipping.
The team and how they connect
The Internal AI Accelerator team is a small, high-impact crew of engineers embedded across Xero's business units. They partner directly with product, engineering, and business teams to design and ship AI workflows in weeks, not months. The team operates with a direct line to senior stakeholders and a genuine mandate to move fast. Together, you are genuinely curious about what works and what doesn't, learning openly from every project and sharing what you discover.
The team is currently working on
The team is expanding from a proof-of-concept phase into building at scale. You will focus on growing the engineering capability across multiple workstreams. Initially, your priorities will be:
Scaling agentic AI delivery across multiple business domains (finance, HR, support, operations)
Building reusable patterns, platforms, and governance frameworks that other teams can adopt
Designing and implementing the technical architecture for enterprise AI deployments
Establishing best practices for AI safety, evaluation, and operations at scale
Where and how you can work
This role is based in Sydney. You will work in a hybrid model with core collaboration days in the office. Xero supports flexible ways of working, and regular "boost days" bring our ANZ teams together for connection and planning.
Here are some of the things we are looking for
You bring solid engineering credibility, ideally from shipping production software at scale, so you can make sound technical decisions and earn your team's respect without needing to code day-to-day.
Your approach to strategy is pragmatic: you can move fast without all the answers, turning vague problems into clear scope, and pivoting when the situation changes.
You will Go Bold in how you lead: giving your team ownership, pushing back on processes that slow you down, and creating space for innovation alongside delivery.
You demonstrate genuine curiosity about your people and a commitment to coaching them up. You leave your team knowing more than when they joined.
You show comfort bridging technical and non-technical worlds, translating between engineers and business stakeholders without losing nuance on either side.
Apply even if your experience isn't a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team.
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