# Lead Engineer - AI Workflows
**Company:** [Xero](https://scaleengineer.com/companies/xero)
Lead Engineer - AI Workflows at Xero is a forward-deployed engineering role focused on designing, building, and operationalizing agentic AI workflows across the organization. You will partner with internal business teams to transform how Xero operates by creating intelligent automation solutions using LLMs like Claude and Gemini, integrated with enterprise platforms such as Salesforce, Workday, Slack, and NetSuite. This role requires deep expertise in AI systems, production API development, and cloud infrastructure, combined with strong technical leadership and stakeholder engagement capabilities.
**Role:** Lead Engineer
**Seniority:** Lead
**Locations:** CAN: Vancouver (333 Seymour St)
**Salary:** 240000–260000 CAD
[Apply](https://jobs.ashbyhq.com/xero/29b71925-11ff-4ed1-b515-50daab030565)
Canonical: https://scaleengineer.com/jobs/xero/lead-engineer-ai-workflows
---
## Responsibilities

- Design and Iterate AI Agent Solutions: Architect and implement agentic AI workflows and intelligent automation systems using large language models such as Claude and Gemini. Employ rapid experimentation methodologies and iterative development practices to evolve AI agents from concept through production deployment, incorporating feedback from business stakeholders and domain experts to optimize performance and user adoption.
- Enterprise Platform Integration: Integrate AI systems and automation workflows with core enterprise applications including Salesforce, Workday, Slack, and NetSuite. Develop robust API connections, webhook implementations, and data pipeline orchestrations that enable seamless end-to-end automation while maintaining system reliability and data integrity across distributed platforms.
- Establish Reusable Automation Patterns: Define, document, and implement standardized automation patterns, shared templates, and best practices for AI-driven workflows. Create a reusable component library and framework that empowers business teams and other engineers to build, deploy, and maintain intelligent automation solutions independently, accelerating adoption across the organization.
- Build Safety and Governance Frameworks: Develop comprehensive evaluation, monitoring, and observability frameworks for AI-native workflows. Implement security guardrails, auditability measures, and controlled blast radius mechanisms to ensure safe agent operation. Design systems-level safeguards that balance automation velocity with risk mitigation and compliance requirements.
- Lead Production Deployment and Operations: Own the end-to-end delivery lifecycle of AI agents and intelligent automation systems from discovery and design through production operationalization and ongoing maintenance. Establish deployment best practices, incident response protocols, and performance optimization procedures to ensure stable, reliable AI systems serving internal and external stakeholders.
- Technical Leadership and Evangelism: Act as a forward-deployed technical partner embedded within business teams, providing architecture guidance, design reviews, and expert consultation on AI implementation challenges. Evangelize AI capabilities, coach teams on AI fluency through pairing sessions and workshops, and translate complex technical concepts into actionable business outcomes.
- Stakeholder Partnership and Translation: Collaborate closely with product owners, subject matter experts, and business leaders to identify automation opportunities and pain points. Translate complex, unstructured business workflows into elegant technical requirements, conduct discovery sessions, and present technical tradeoffs and solutions to non-technical audiences with clarity and business acumen.

## Requirements

### education

- {"name":"Computer Science or Related Discipline","description":"Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, or equivalent discipline providing foundational knowledge in algorithms, data structures, systems design, and software engineering principles."}

### technical

- {"name":"Production Application Development","description":"Demonstrated expertise building, deploying, and maintaining production-grade applications and automation systems. Proficiency in managing the full application lifecycle including architecture design, scalable deployment, monitoring, incident response, and operational maintenance in cloud environments."}
- {"name":"Large Language Model and AI Agent Development","description":"Hands-on experience designing and implementing AI-driven solutions such as autonomous agents, AI copilots, or retrieval-augmented generation (RAG) systems using LLMs like Claude, Gemini, GPT, or similar models. Understanding of prompt engineering, agent orchestration frameworks, and agentic AI patterns."}
- {"name":"API Development and Integration","description":"Strong proficiency with RESTful API design, development, and integration patterns. Expertise in consuming third-party APIs, managing webhooks, handling authentication flows, and building robust integration layers between disparate systems at scale."}
- {"name":"Python or TypeScript Programming","description":"Advanced proficiency in Python or TypeScript as primary development languages. Ability to write clean, maintainable, performant code with strong software engineering practices including testing, documentation, and design patterns suitable for production environments."}
- {"name":"Cloud Infrastructure and DevOps","description":"Practical experience with cloud platforms and infrastructure-as-code principles. Familiarity with containerization, serverless architectures, deployment pipelines, monitoring, logging, and cloud-native development practices for building scalable distributed systems."}
- {"name":"Systems Thinking and Architecture","description":"Ability to design systems with security, auditability, and risk management at the forefront. Experience implementing systematic approaches to agent design, error handling, blast radius containment, and architectural resilience patterns for mission-critical automation."}
- {"name":"Enterprise Platform Knowledge","description":"Understanding of enterprise software ecosystems and experience integrating with platforms such as Salesforce, Workday, NetSuite, or similar complex business systems. Familiarity with enterprise data models, security requirements, and integration patterns."}

### experience

- {"name":"Production System Operations","description":"Track record of building and operating mission-critical applications in production environments with responsibility for reliability, performance, and incident management. Experience managing the operational aspects of deployed systems including monitoring, troubleshooting, and optimization."}
- {"name":"AI Solution Delivery","description":"Demonstrated success delivering end-to-end AI-powered solutions from ideation through production deployment. Proven ability to navigate the complexities of AI development including model selection, prompt refinement, performance evaluation, and iterative improvement based on real-world usage patterns."}
- {"name":"Cross-Functional Collaboration","description":"Extensive experience partnering with non-technical stakeholders including business leaders, product managers, and subject matter experts. Track record of translating business requirements into technical specifications and communicating technical concepts effectively to diverse audiences."}
- {"name":"Technical Mentorship and Leadership","description":"Demonstrated ability to uplift teammates and stakeholders through coaching, pairing sessions, and knowledge sharing. Experience establishing engineering best practices, conducting technical reviews, and fostering a culture of continuous learning and improvement."}

## Skills

### required

- {"name":"Python Programming","description":"Expert-level proficiency in Python including async programming, SDK development, and production application patterns for AI and workflow automation systems."}
- {"name":"TypeScript/JavaScript","description":"Strong capability in TypeScript or JavaScript for building scalable backend services, API development, and modern cloud-native applications in AI automation contexts."}
- {"name":"Large Language Models and Claude/Gemini APIs","description":"Practical expertise using Claude, Gemini, or similar LLM APIs. Understanding of model capabilities, token management, prompt optimization, and integration into production systems."}
- {"name":"Workflow Orchestration and Agentic AI","description":"Experience with AI agent frameworks, orchestration tools, MCP (Model Context Protocol), and patterns for building autonomous systems that make decisions and take actions."}
- {"name":"REST API Development and Integration","description":"Proficiency designing and consuming REST APIs, implementing webhook handlers, managing authentication, and building robust integration layers between systems."}
- {"name":"Cloud Platforms (AWS/GCP/Azure)","description":"Practical experience deploying and managing applications on major cloud platforms including serverless services, containerization, and infrastructure-as-code approaches."}
- {"name":"Systems Design and Architecture","description":"Ability to design distributed systems with consideration for security, reliability, observability, scalability, and risk management in the context of AI-driven automation."}
- {"name":"Stakeholder Communication","description":"Strong ability to articulate technical concepts to non-technical audiences, gather requirements from business stakeholders, and translate business problems into technical solutions."}

### preferred

- {"name":"Salesforce and Enterprise CRM Integration","description":"Prior experience integrating with Salesforce including API calls, data synchronization, and workflow automation within CRM contexts."}
- {"name":"Workday Integration and HRIS Systems","description":"Familiarity with Workday or similar HRIS platforms and experience building integrations or automations involving HR data and processes."}
- {"name":"NetSuite Integration","description":"Experience with NetSuite ERP platform integration, including API usage, data modeling, and automation of financial and operational workflows."}
- {"name":"Slack API and Messaging Automation","description":"Background building Slack apps, bots, or integrations that automate workflows and enable human-AI collaboration through messaging interfaces."}
- {"name":"RAG and Vector Databases","description":"Experience implementing retrieval-augmented generation systems, working with vector databases, and knowledge management for AI agents."}
- {"name":"Agent Evaluation and LLMOps","description":"Familiarity with evaluation frameworks for AI agents, monitoring LLM performance, testing methodologies, and operational practices for AI systems in production."}
- {"name":"Containerization and Kubernetes","description":"Hands-on experience with Docker, containerization, and container orchestration platforms for deploying and scaling production applications."}
- {"name":"Internal Developer Tooling and SDKs","description":"Experience building or maintaining internal developer tools, libraries, or SDKs that enable other engineers to build solutions more effectively."}

## Tech stack

### tools

- {"name":"Salesforce API","description":"Integration point for automating CRM workflows, syncing lead and customer data, and driving intelligent customer engagement through AI agents."}
- {"name":"Workday API","description":"HRIS integration enabling automation of HR processes, employee data management, and intelligent workforce orchestration across the organization."}
- {"name":"NetSuite API","description":"ERP integration for automating financial processes, supply chain workflows, and business intelligence automation powered by AI agents."}
- {"name":"Slack API","description":"Messaging platform integration enabling AI agents to communicate with users, receive commands, and orchestrate workflows through conversational interfaces."}
- {"name":"Git / GitHub","description":"Version control and collaborative development platform for managing codebase, code review workflows, and deployment automation for AI systems."}
- {"name":"Docker","description":"Containerization platform for packaging AI applications, ensuring consistent deployment across development, testing, and production environments."}
- {"name":"Kubernetes / ECS","description":"Container orchestration platforms for managing deployment, scaling, and operational management of AI workflow services at enterprise scale."}
- {"name":"Terraform / Infrastructure-as-Code","description":"Infrastructure automation tools for provisioning and managing cloud resources consistently and repeatably across environments."}
- {"name":"Datadog / New Relic","description":"Observability and monitoring platforms for tracking AI agent performance, detecting anomalies, and troubleshooting issues in production systems."}

### others

- {"name":"RESTful API Design","description":"Expertise in designing, building, and consuming RESTful APIs with proper error handling, authentication, rate limiting, and integration patterns."}
- {"name":"Webhook Development","description":"Experience building webhook receivers and handlers for real-time event processing, system integrations, and AI workflow triggering."}
- {"name":"Authentication and Security Patterns","description":"Knowledge of OAuth2, JWT, API key management, and secure authentication patterns for integrating disparate enterprise systems safely."}
- {"name":"Prompt Engineering and LLM Optimization","description":"Techniques for designing effective prompts, managing token usage, optimizing model selection, and iteratively improving AI system performance."}
- {"name":"Agentic AI Patterns","description":"Understanding of agent design patterns including tool use, function calling, planning, reasoning, and controlled autonomy in AI systems."}
- {"name":"Observability and Monitoring","description":"Implementation of comprehensive logging, tracing, metrics collection, and alerting for production AI systems and automation workflows."}

### databases

- {"name":"PostgreSQL","description":"Primary relational database for storing workflow state, agent execution logs, audit trails, and operational data in AI automation systems."}
- {"name":"Vector Databases (Pinecone/Weaviate/Milvus)","description":"Specialized databases for storing embeddings and enabling semantic search capabilities in retrieval-augmented generation systems supporting AI agents."}
- {"name":"Redis","description":"In-memory data store used for caching, session management, workflow orchestration state, and real-time data synchronization in AI systems."}
- {"name":"DynamoDB / Firestore","description":"NoSQL databases used for flexible schema requirements, high-throughput logging, and distributed state management in cloud-native AI workflows."}

### languages

- {"name":"Python","description":"Primary language for AI agent development, workflow automation, LLM integration, and backend service implementation at Xero's AI Accelerator."}
- {"name":"TypeScript","description":"Secondary language for building scalable backend services, API development, and cloud-native applications supporting AI workflows."}
- {"name":"JavaScript","description":"Used alongside TypeScript for full-stack development and Node.js-based backend services in the AI automation platform."}

### frameworks

- {"name":"LangChain","description":"Framework for building LLM applications, managing agent workflows, and orchestrating interactions between multiple AI models and external tools."}
- {"name":"Claude API / Anthropic SDK","description":"Xero's primary LLM provider offering advanced reasoning capabilities, long context windows, and reliable performance for agentic AI workflows."}
- {"name":"Gemini API / Google Generative AI","description":"Secondary LLM provider integrated with Xero's AI stack for multimodal capabilities and diverse model options in automation scenarios."}
- {"name":"Model Context Protocol (MCP)","description":"Protocol for standardizing how AI agents interact with external tools, APIs, and resources in a safe, composable manner across Xero's ecosystem."}
- {"name":"Express.js / FastAPI","description":"Backend frameworks for building API servers, webhook handlers, and microservices supporting AI workflow orchestration and integration."}

## Benefits

### benefits

## Compensation

- **max:** 260000
- **min:** 240000
- **currency:** CAD
- **stockOptions:** true

## Interview process

### steps

## 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.

**Compensation Philosophy**

At Xero, we value the impact and skills you bring to the team. We don’t just hire for a role; we invest in people. We believe in a **Total Package** philosophy - which means your value isn't just a single number on a paycheque. While base salary is a core component, we look at your compensation through a holistic lens that includes equity, performance incentives, and world-class benefits.

The base salary range for this role in Canada is **$240,000 - $260,000 CAD.**

Please note that this range represents base salary only. We believe in rewarding our people for their total contribution, which is why we look at compensation through a holistic lens. In addition to base pay, your total package may include:

* **Variable Pay:** Eligibility commissions or equity based on role and performance.
* **Comprehensive Benefits:** World-class health, wellness, and retirement programs.
* **Xero Perks:** [Inside Xero](https://careers.xero.com/inside-xero/benefits-wellbeing/) Explore our full suite of benefits, from wellbeing initiatives to professional development.

_Individual pay is determined by various factors, including geography, level of experience, and the specific skills you bring to the role_