# Lead Engineer - Applied AI
**Company:** [Xero](https://scaleengineer.com/companies/xero)
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.
**Role:** Lead Engineer
**Seniority:** Lead
**Locations:** AU: Sydney (45 Clarence St)
**Salary:** 140000–200000 NZD
[Apply](https://jobs.ashbyhq.com/xero/476734a4-efd8-488c-ac6a-20c52bc07a5d)
Canonical: https://scaleengineer.com/jobs/xero/lead-engineer-applied-ai
---
## 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.

## Requirements

### education

- {"name":"Computer Science or Engineering Degree","description":"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)."}

### technical

- {"name":"LLM and AI Agent Development","description":"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."}
- {"name":"Production Application Development and Operations","description":"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."}
- {"name":"Programming Language Mastery","description":"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."}
- {"name":"Enterprise Platform Integration","description":"Experience integrating with enterprise platforms such as Salesforce, Workday, Slack, or NetSuite, with understanding of OAuth, API authentication, data mapping, and enterprise integration patterns."}
- {"name":"Systems Thinking and AI Safety","description":"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."}

### experience

- {"name":"AI Engineering Track Record","description":"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."}
- {"name":"Technical Leadership and Mentorship","description":"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."}
- {"name":"Cross-Functional Stakeholder Management","description":"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."}
- {"name":"High-Velocity Product Development","description":"Experience working in fast-paced, startup-like environments with rapid experimentation cycles, shipping features quickly while maintaining code quality and operational excellence."}

## Skills

### required

- {"name":"Python or TypeScript Programming","description":"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."}
- {"name":"LLM Platform Expertise","description":"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."}
- {"name":"API Design and Integration","description":"Strong proficiency designing, building, and consuming RESTful and asynchronous APIs, with understanding of webhooks, streaming protocols, and event-driven architecture patterns."}
- {"name":"Cloud Infrastructure and DevOps","description":"Working knowledge of cloud platforms (AWS, GCP, or Azure), containerization (Docker), and deployment pipelines, with ability to design scalable, resilient systems."}
- {"name":"Systems Architecture and Security","description":"Ability to design systems with security, auditability, and observability in mind, including implementing access controls, audit logging, and monitoring frameworks."}
- {"name":"Communication and Technical Evangelism","description":"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

- {"name":"Model Context Protocol (MCP) Experience","description":"Familiarity with emerging AI standards like Model Context Protocol for building extensible, composable AI systems and tool use patterns."}
- {"name":"Enterprise SaaS Platform Experience","description":"Prior experience integrating with or extending Salesforce, Workday, Slack, or NetSuite, including understanding of their data models, APIs, and ecosystem."}
- {"name":"Evaluation and Monitoring Frameworks","description":"Experience building evaluation frameworks for LLM applications, implementing observability for AI systems, and defining metrics for AI agent performance and safety."}
- {"name":"Workflow Orchestration Tools","description":"Hands-on experience with workflow automation platforms, process mining tools, or business process management (BPM) systems for designing intelligent automations."}
- {"name":"Open-Source AI Ecosystem","description":"Familiarity with open-source frameworks like LangChain, LlamaIndex, CrewAI, or similar tools for building production AI applications."}
- {"name":"Financial Software Domain Knowledge","description":"Background in accounting, finance, or SaaS fintech products, providing domain context relevant to Xero's accounting platform ecosystem."}

## Tech stack

### tools

- {"name":"Salesforce APIs","description":"Enterprise CRM platform integration for customer relationship data and automation workflows."}
- {"name":"Workday APIs","description":"Human capital management platform for employee data, payroll, and organizational hierarchy integration."}
- {"name":"Slack APIs","description":"Workplace messaging platform for building conversational AI, bots, and notification workflows."}
- {"name":"NetSuite","description":"Cloud-based ERP system for financial management and business process integration."}
- {"name":"Docker","description":"Containerization platform for packaging and deploying AI applications and microservices."}
- {"name":"Git & GitHub","description":"Version control and collaborative development platform for managing code and team workflows."}

### others

- {"name":"Model Context Protocol (MCP)","description":"Emerging standard for building extensible, composable AI systems with standardized tool use and context management."}
- {"name":"Prompt Engineering Best Practices","description":"Techniques for optimizing LLM inputs, managing temperature and parameters, and implementing few-shot learning strategies."}
- {"name":"AI Agent Design Patterns","description":"Architectural patterns for building autonomous agents with tool use, planning, and decision-making capabilities."}
- {"name":"Observability and Monitoring","description":"Tools and practices for monitoring AI system performance, tracking token usage, latency, and cost optimization."}

### databases

- {"name":"PostgreSQL","description":"Reliable relational database for storing application state, audit logs, and enterprise data with ACID guarantees."}
- {"name":"Vector Databases","description":"Specialized databases like Pinecone, Weaviate, or Postgres pgvector for storing and querying embeddings in RAG systems."}

### languages

- {"name":"Python","description":"Primary language for AI/ML development, data processing, and backend automation workflows at scale."}
- {"name":"TypeScript","description":"Type-safe alternative for building AI applications, APIs, and cloud functions with strong tooling and ecosystem support."}

### frameworks

- {"name":"Claude SDK","description":"Anthropic's official SDK for building applications with Claude LLM, including support for tool use, vision capabilities, and streaming responses."}
- {"name":"Gemini API","description":"Google's LLM platform for building AI agents and generative applications with multi-modal capabilities."}
- {"name":"LangChain","description":"Popular framework for orchestrating LLM chains, managing prompt templates, memory, and building complex AI workflows."}
- {"name":"LlamaIndex","description":"Framework for building retrieval-augmented generation (RAG) systems and connecting LLMs to external data sources."}

## Benefits

### benefits

- {"name":"Hybrid Work Flexibility","description":"Blend of remote work autonomy with regular in-office collaboration days at modern office spaces designed for team bonding, brainstorming, and cross-functional connection."}
- {"name":"Equity Participation","description":"Stock options enabling you to share in Xero's long-term success as a publicly-listed company on the ASX and NZSX."}
- {"name":"Professional Development and Learning","description":"Access to professional development budgets, conference attendance, and training programs to stay current with rapidly evolving AI technologies and industry best practices."}
- {"name":"Collaborative Peer Learning Culture","description":"Work alongside world-class engineers in a high-velocity team environment with emphasis on knowledge sharing, pair programming, and continuous growth."}
- {"name":"Global Impact and Scale","description":"Opportunity to shape how a global organization with millions of small business customers harnesses AI, with direct visibility into your solutions' business impact."}
- {"name":"Modern Tech Infrastructure","description":"Access to cutting-edge cloud platforms, AI tools, and development infrastructure with generous compute budgets for experimentation and production deployments."}
- {"name":"Health and Wellness Programs","description":"Comprehensive health insurance, wellness initiatives, and employee assistance programs supporting physical and mental health."}

## Compensation

- **max:** 200000
- **min:** 140000
- **currency:** NZD
- **stockOptions:** true

## Interview process

### steps

- {"name":"Initial Screening and Technical Alignment Call","description":"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."}
- {"name":"Technical AI Assessment","description":"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."}
- {"name":"Systems Design and Architecture Interview","description":"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."}
- {"name":"Technical Leadership and Communication Round","description":"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."}
- {"name":"Cross-Functional Collaboration Discussion","description":"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."}
- {"name":"Leadership and Cultural Fit","description":"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 description
**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.