Lead Engineer - AI Workflows

Lead Engineer · Lead · Full Time

CAN: Vancouver (333 Seymour St)CAD 240k – 260k1d ago
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Role

What you'll do.

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.

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.

Qualifications

What we look for.

Technical

  • Production Application Development

    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.

  • Large Language Model and AI Agent Development

    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.

  • API Development and Integration

    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.

  • Python or TypeScript Programming

    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.

  • Cloud Infrastructure and DevOps

    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.

  • Systems Thinking and Architecture

    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.

  • Enterprise Platform Knowledge

    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.

Education

  • Computer Science or Related Discipline

    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.

Experience

  • Production System Operations

    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.

  • AI Solution Delivery

    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.

  • Cross-Functional Collaboration

    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.

  • Technical Mentorship and Leadership

    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

  • Python Programming

    Expert-level proficiency in Python including async programming, SDK development, and production application patterns for AI and workflow automation systems.

  • TypeScript/JavaScript

    Strong capability in TypeScript or JavaScript for building scalable backend services, API development, and modern cloud-native applications in AI automation contexts.

  • Large Language Models and Claude/Gemini APIs

    Practical expertise using Claude, Gemini, or similar LLM APIs. Understanding of model capabilities, token management, prompt optimization, and integration into production systems.

  • Workflow Orchestration and Agentic AI

    Experience with AI agent frameworks, orchestration tools, MCP (Model Context Protocol), and patterns for building autonomous systems that make decisions and take actions.

  • REST API Development and Integration

    Proficiency designing and consuming REST APIs, implementing webhook handlers, managing authentication, and building robust integration layers between systems.

  • Cloud Platforms (AWS/GCP/Azure)

    Practical experience deploying and managing applications on major cloud platforms including serverless services, containerization, and infrastructure-as-code approaches.

  • Systems Design and Architecture

    Ability to design distributed systems with consideration for security, reliability, observability, scalability, and risk management in the context of AI-driven automation.

  • Stakeholder Communication

    Strong ability to articulate technical concepts to non-technical audiences, gather requirements from business stakeholders, and translate business problems into technical solutions.

Preferred

  • Salesforce and Enterprise CRM Integration

    Nice to have

    Prior experience integrating with Salesforce including API calls, data synchronization, and workflow automation within CRM contexts.

  • Workday Integration and HRIS Systems

    Nice to have

    Familiarity with Workday or similar HRIS platforms and experience building integrations or automations involving HR data and processes.

  • NetSuite Integration

    Nice to have

    Experience with NetSuite ERP platform integration, including API usage, data modeling, and automation of financial and operational workflows.

  • Slack API and Messaging Automation

    Nice to have

    Background building Slack apps, bots, or integrations that automate workflows and enable human-AI collaboration through messaging interfaces.

  • RAG and Vector Databases

    Nice to have

    Experience implementing retrieval-augmented generation systems, working with vector databases, and knowledge management for AI agents.

  • Agent Evaluation and LLMOps

    Nice to have

    Familiarity with evaluation frameworks for AI agents, monitoring LLM performance, testing methodologies, and operational practices for AI systems in production.

  • Containerization and Kubernetes

    Nice to have

    Hands-on experience with Docker, containerization, and container orchestration platforms for deploying and scaling production applications.

  • Internal Developer Tooling and SDKs

    Nice to have

    Experience building or maintaining internal developer tools, libraries, or SDKs that enable other engineers to build solutions more effectively.

Tech stack

Languages

PythonTypeScriptJavaScript

Frameworks

LangChainClaude API / Anthropic SDKGemini API / Google Generative AIModel Context Protocol (MCP)Express.js / FastAPI

Databases

PostgreSQLVector Databases (Pinecone/Weaviate/Milvus)RedisDynamoDB / Firestore

Tools

Salesforce APIWorkday APINetSuite APISlack APIGit / GitHubDockerKubernetes / ECSTerraform / Infrastructure-as-CodeDatadog / New Relic

Other

RESTful API DesignWebhook DevelopmentAuthentication and Security PatternsPrompt Engineering and LLM OptimizationAgentic AI PatternsObservability and Monitoring

Compensation

Pay and benefits.

Base·CAD 240,000 – 260,000

Equity·Stock options

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.

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 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

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