Scale Engineer

Lead Engineer - Applied AI

Lead Engineer · Lead · Full Time

AU: Sydney (45 Clarence St)NZD 140k – 200k2d ago
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Role

What you'll do.

Join Xero's Internal AI Accelerator Squad as a Lead Engineer - Applied AI, where you'll architect and deploy production-grade agentic AI workflows that transform how enterprise teams work. This forward-deployed engineering role combines hands-on LLM expertise with systems-thinking and technical leadership to establish AI governance patterns and reusable automation frameworks across a global organization. You'll partner with Salesforce, Workday, and other enterprise platforms while coaching internal stakeholders and defining the blueprint for safe, effective AI adoption.

Responsibilities

  • Design and Deploy Production Agentic AI Systems: Design, iterate, and operationalize AI agents and workflow orchestrations from discovery through production deployment, utilizing LLM platforms such as Claude and Gemini while ensuring systems-thinking principles around security, auditability, and controlled blast radius.
  • Lead Enterprise AI Integration Architecture: Architect seamless integrations between AI systems and core enterprise platforms including Salesforce, Workday, Slack, and NetSuite, managing APIs, webhooks, and cloud infrastructure to enable cross-functional automation at scale.
  • Establish AI Governance and Safety Frameworks: Build and maintain evaluation and monitoring frameworks to measure AI agent performance, ensure safety of AI-native workflows, and define guardrails, patterns, and best practices for intelligent automation across the organization.
  • Drive Adoption Through Technical Evangelism: Act as a forward-deployed engineer embedded within business teams, coaching non-technical stakeholders through pairing sessions, workshops, and clear communication to elevate AI fluency and translate business pain points into technical solution designs.
  • Develop Reusable Automation Assets: Create shared templates, SDKs, and reusable automation patterns that enable broader business teams to harness AI safely and effectively, reducing manual toil and establishing standardized approaches to workflow automation.
  • Collaborate with Product and Subject Matter Experts: Work in high-velocity sprints with product owners and domain experts, focusing on rapid experimentation and iterative development to transform complex, messy workflows into elegant, automated AI-driven solutions.

Qualifications

What we look for.

Technical

  • LLM and AI Agent Development

    Hands-on experience building and deploying AI-driven solutions including AI agents, copilots, and retrieval-augmented generation (RAG) systems using production LLM platforms such as Claude, Gemini, or equivalent models, with demonstrated expertise in prompt engineering and model fine-tuning.

  • Production Application Development and Operations

    Extensive experience building, deploying, and operating applications and automations in production environments at scale, with strong proficiency in managing APIs, cloud infrastructure, monitoring, and production debugging.

  • Programming Language Mastery

    Strong hands-on proficiency in Python or TypeScript, with demonstrated ability to write maintainable, scalable code and comfort navigating SDKs, webhooks, and asynchronous programming patterns.

  • Enterprise Platform Integration

    Experience integrating with enterprise platforms such as Salesforce, Workday, Slack, or NetSuite, with understanding of OAuth, API authentication, data mapping, and enterprise integration patterns.

  • Systems Thinking and AI Safety

    Demonstrated ability to design distributed systems with security, observability, auditability, and controlled blast radius at the forefront, including experience implementing retry logic, error handling, and system resilience patterns.

Education

  • Computer Science or Engineering Degree

    Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or equivalent professional experience and demonstrated technical capability (degree not strictly required if strong portfolio exists).

Experience

  • AI Engineering Track Record

    Minimum 3-5 years of professional experience in AI/ML engineering roles, with proven ability to deliver end-to-end AI projects from concept to production, including at least 2+ years working with LLMs or modern generative AI technologies.

  • Technical Leadership and Mentorship

    Demonstrated experience leading technical initiatives, mentoring engineers, and establishing coding standards or architectural patterns, with a track record of elevating team capability and sharing knowledge.

  • Cross-Functional Stakeholder Management

    Proven ability to partner effectively with non-technical stakeholders including product managers, business analysts, and C-suite executives, translating complex technical concepts and business requirements into actionable solutions.

  • High-Velocity Product Development

    Experience working in fast-paced, startup-like environments with rapid experimentation cycles, shipping features quickly while maintaining code quality and operational excellence.

Skills

Required

  • Python or TypeScript Programming

    Production-grade proficiency in at least one of Python or TypeScript, with ability to write clean, maintainable, and scalable code in both synchronous and asynchronous contexts.

  • LLM Platform Expertise

    Hands-on experience with Claude, Gemini, or equivalent production LLM APIs, including prompt engineering, model selection, cost optimization, and handling model rate limits and reliability.

  • API Design and Integration

    Strong proficiency designing, building, and consuming RESTful and asynchronous APIs, with understanding of webhooks, streaming protocols, and event-driven architecture patterns.

  • Cloud Infrastructure and DevOps

    Working knowledge of cloud platforms (AWS, GCP, or Azure), containerization (Docker), and deployment pipelines, with ability to design scalable, resilient systems.

  • Systems Architecture and Security

    Ability to design systems with security, auditability, and observability in mind, including implementing access controls, audit logging, and monitoring frameworks.

  • Communication and Technical Evangelism

    Exceptional ability to explain complex technical concepts to non-technical stakeholders, mentor junior engineers, and build consensus around technical decisions through clear documentation and presentation skills.

Preferred

  • Model Context Protocol (MCP) Experience

    Nice to have

    Familiarity with emerging AI standards like Model Context Protocol for building extensible, composable AI systems and tool use patterns.

  • Enterprise SaaS Platform Experience

    Nice to have

    Prior experience integrating with or extending Salesforce, Workday, Slack, or NetSuite, including understanding of their data models, APIs, and ecosystem.

  • Evaluation and Monitoring Frameworks

    Nice to have

    Experience building evaluation frameworks for LLM applications, implementing observability for AI systems, and defining metrics for AI agent performance and safety.

  • Workflow Orchestration Tools

    Nice to have

    Hands-on experience with workflow automation platforms, process mining tools, or business process management (BPM) systems for designing intelligent automations.

  • Open-Source AI Ecosystem

    Nice to have

    Familiarity with open-source frameworks like LangChain, LlamaIndex, CrewAI, or similar tools for building production AI applications.

  • Financial Software Domain Knowledge

    Nice to have

    Background in accounting, finance, or SaaS fintech products, providing domain context relevant to Xero's accounting platform ecosystem.

Tech stack

Languages

PythonTypeScript

Frameworks

Claude SDKGemini APILangChainLlamaIndex

Databases

PostgreSQLVector Databases

Tools

Salesforce APIsWorkday APIsSlack APIsNetSuiteDockerGit & GitHub

Other

Model Context Protocol (MCP)Prompt Engineering Best PracticesAI Agent Design PatternsObservability and Monitoring

Compensation

Pay and benefits.

Base·NZD 140,000 – 200,000

Equity·Stock options

Benefits

  • Hybrid Work Flexibility

    Blend of remote work autonomy with regular in-office collaboration days at modern office spaces designed for team bonding, brainstorming, and cross-functional connection.

  • Equity Participation

    Stock options enabling you to share in Xero's long-term success as a publicly-listed company on the ASX and NZSX.

  • Professional Development and Learning

    Access to professional development budgets, conference attendance, and training programs to stay current with rapidly evolving AI technologies and industry best practices.

  • Collaborative Peer Learning Culture

    Work alongside world-class engineers in a high-velocity team environment with emphasis on knowledge sharing, pair programming, and continuous growth.

  • Global Impact and Scale

    Opportunity to shape how a global organization with millions of small business customers harnesses AI, with direct visibility into your solutions' business impact.

  • Modern Tech Infrastructure

    Access to cutting-edge cloud platforms, AI tools, and development infrastructure with generous compute budgets for experimentation and production deployments.

  • Health and Wellness Programs

    Comprehensive health insurance, wellness initiatives, and employee assistance programs supporting physical and mental health.

Process

Interview steps.

  1. 01

    Initial Screening and Technical Alignment Call

    30-minute conversation with recruiter to assess your background, motivation for the role, and alignment with Xero's AI transformation mission. Expect discussion of your LLM project experience and technical interests.

  2. 02

    Technical AI Assessment

    Take-home or live coding challenge focused on building a practical AI application component, such as designing an LLM-based agent, integrating an API, or architecting an evaluation framework. Typically 1-2 hours, designed to reflect real work.

  3. 03

    Systems Design and Architecture Interview

    Whiteboard-style interview (typically 60-90 minutes) discussing how you would design a production-grade AI system at Xero's scale. Expect questions on scalability, safety, security, and enterprise integration patterns.

  4. 04

    Technical Leadership and Communication Round

    Interview with a senior engineer or tech lead to assess communication clarity, mentoring ability, and how you partner with non-technical stakeholders. May include discussing past projects and how you've elevated team AI literacy.

  5. 05

    Cross-Functional Collaboration Discussion

    Conversation with a Product Manager or Business Lead to evaluate ability to translate complex business problems into technical solutions and collaborate effectively across organizational boundaries.

  6. 06

    Leadership and Cultural Fit

    Final interview with hiring manager or senior leader to assess long-term potential, leadership philosophy, and cultural alignment with Xero's values of innovation, customer focus, and collaborative problem-solving.

Full posting

Original listing.

The role / impact

As a Lead Engineer within the Internal AI Accelerator Squad, you will be at the forefront of Xero’s transformation into an AI-native company. You will act as a forward-deployed engineer, embedding yourself within various internal business teams to co-design and operationalise agentic AI workflows that remove manual toil and fundamentally reshape how our people work end-to-end.

Your impact extends beyond the code; you will lead the delivery of high-stakes AI agents from discovery to production, while acting as a technical partner and evangelist. By defining the patterns, guardrails, and tooling for intelligent automation, you will create the blueprint that enables the rest of Xero to harness the power of AI safely and effectively.

The team / how they connect

You will join a dedicated, high-velocity squad focused on boosting the adoption of agentic AI and intelligent automation across the global business. The team connects through a shared mission of rapid experimentation and "vibe-coding," working closely with product owners and SMEs to turn complex, messy workflows into elegant, automated solutions.

The team is currently working on / Initially, you will focus on

  • Designing and iterating on AI agents and workflow orchestrations using tools like Claude, Gemini, and MCP.

  • Integrating AI systems with core enterprise platforms including Salesforce, Workday, Slack, and NetSuite.

  • Developing reusable automation patterns and shared templates to be used by the business

  • Building evaluation and monitoring frameworks to measure performance and ensure the safety of AI-native workflows.

Where and how you can work

At Xero, we embrace a hybrid way of working that prioritises both flexibility and meaningful connection. You will have the autonomy to work from home, supported by regular boost days in our modern office spaces designed to foster collaboration, brainstorming, and team bonding.

Here are some of the things we are looking for

  • You bring a wealth of experience in building and operating applications or automations within production environments, particularly involving APIs and cloud infrastructure.

  • Your background includes hands-on delivery of AI-driven solutions such as agents, copilots, or RAG systems using LLMs like Claude or Gemini.

  • You possess proficiency in programming languages such as Python or TypeScript and feel comfortable navigating SDKs and webhooks.

  • A systems-thinking approach is part of your toolkit, allowing you to design agents with security, auditability, and controlled blast radius at the forefront.

  • You have a track record of partnering with non-technical stakeholders to translate business pain points into technical solution designs.

  • You are a natural coach who enjoys uplifting the AI fluency of those around you through pairing, workshops, and clear communication.

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