Senior Engineer - AI Agentic

Xero2 weeks ago

Location

AU: Melbourne: (260 Burwood Rd)

Type

Full Time

Salary

AUD 160,000 – 220,000

Level

Senior

Role

Senior Engineer

Posted

Jul 6, 2026

Full TimeSenior

The role

Summary

Senior Software Engineer specializing in AI enablement at Xero, leading the design and implementation of internal AI tools, platforms, and distribution systems that empower engineers across the organization. This role combines hands-on software engineering expertise with architectural influence, requiring deep production discipline and strategic thinking about AI-native tooling and agent-based systems.

What you'll do

Architect and Build AI Distribution Platform: Design and implement an internal distribution platform for AI tools and agent skills used across Xero's engineering organization. This includes creating the underlying infrastructure, versioning systems, and dependency management that allow engineers to discover, integrate, and deploy AI-native capabilities securely and reliably.

Develop Internal Skills Marketplace: Build and maintain an internal skills marketplace where engineering teams can browse, discover, and adopt pre-built AI agent skills and capabilities. Establish governance models, quality standards, and documentation frameworks that ensure marketplace quality and usability across the organization.

Establish AI Engineering Best Practices: Create comprehensive guidance, documentation, and training materials for authoring agent skills and building AI-native solutions. Develop best practice standards for prompt engineering, agent orchestration, error handling, and monitoring that the wider engineering organization can adopt consistently.

Lead Early-Access Technology Integration: Collaborate directly with strategic vendors including AWS, Microsoft, and GitHub to evaluate, integrate, and optimize early-access AI technologies not yet available in public markets. Provide technical feedback and contribute to shaping these platforms based on real-world production usage patterns at Xero.

Implement Production Reliability Systems: Own end-to-end reliability for all platforms and tools built by the team, including writing comprehensive runbooks, establishing monitoring and alerting strategies, designing rollback procedures, and maintaining incident response protocols. Ensure all systems meet enterprise-grade reliability standards from day one.

Mentor and Guide AI Engineering Journey: Work closely with product engineering teams to help them adopt AI-native approaches effectively. Provide technical mentorship, code reviews, and architectural guidance as teams integrate AI tooling into their workflows, helping accelerate organizational learning and adoption.

Drive Technical Decision-Making: Participate in strategic technical decision-making for the AI Enablement platform direction. Challenge proposals constructively, evaluate technology options, and help the team make well-informed architectural choices that balance innovation with production stability.

What we look for

Technical

Production-Grade Software EngineeringDemonstrated expertise building reliable, production systems with comprehensive monitoring, runbooks, and incident response capabilities. Must understand operational excellence principles including observability, alerting, rollback strategies, and graceful degradation.

C# and .NET PlatformStrong hands-on experience with C# and the .NET ecosystem. Comfortable building scalable backend services, APIs, and distributed systems using modern .NET patterns and frameworks. Experience with async/await patterns and performance optimization in .NET environments.

AWS Cloud ArchitectureSolid understanding of AWS services including EC2, RDS, Lambda, SQS, S3, CloudWatch, and IAM. Ability to design and implement cloud-native architectures, understand cost optimization, and implement security best practices within AWS environments.

AI and Agentic Systems FundamentalsFoundational knowledge of large language models, prompt engineering principles, and agent orchestration patterns. Understanding of AI workflow design, tool use in AI systems, and integration patterns for LLM-based applications in production environments.

Platform and Developer ToolsExperience building internal platforms, developer tools, or infrastructure that other engineers depend on. Understanding of API design, extensibility patterns, discoverability mechanisms, and developer experience optimization for tool adoption.

Python and TypeScriptWorking familiarity with Python and TypeScript for AI tooling and scripting. Ability to write quick prototypes, automation scripts, and tools that complement the primary .NET stack in specialized domains like machine learning or frontend tooling.

Education

Computer Science or Related FieldBachelor's degree in Computer Science, Software Engineering, Mathematics, Physics, or equivalent practical software engineering experience. Advanced degrees or self-taught developers with strong portfolios are equally valued.

Experience

Senior-Level Software EngineeringMinimum 5-7 years of professional software engineering experience with at least 2-3 years at a senior level. Track record of successfully shipping production systems, mentoring junior engineers, and making significant architectural contributions to codebases.

Building Developer Platforms and ToolsProven experience designing and implementing tools, frameworks, or platforms that other engineers actively use and depend on. Experience shipping features that meaningfully improve developer productivity or enable new engineering capabilities at scale.

Cross-Functional CollaborationExperience working effectively with product managers, other engineers, and external stakeholders. Demonstrated ability to communicate technical ideas clearly, gather requirements from diverse audiences, and drive alignment across teams.

Distributed Systems and ScalabilityExperience designing systems for reliability and scale. Understanding of distributed system patterns, eventual consistency, microservices architecture, and patterns for handling high-throughput scenarios.

Emerging Technology EvaluationTrack record of learning and working with emerging or early-stage technologies. Comfort with rapid change, ability to evaluate new tools and frameworks objectively, and willingness to experiment with novel approaches while maintaining production discipline.

Skills

Required skills

C#Professional proficiency in C# with deep understanding of language features, LINQ, async/await patterns, and performance optimization techniques.

.NET Framework/CoreHands-on experience with .NET framework or .NET Core for building scalable backend services, APIs, and system components.

AWSPractical experience deploying and managing applications on AWS with understanding of core services like EC2, Lambda, RDS, and observability tools.

Production EngineeringDeep expertise in reliability, monitoring, logging, alerting, and incident response. Understanding of SLOs, SLAs, and operational excellence practices.

API DesignExperience designing clean, intuitive APIs and developer interfaces. Understanding of REST principles, versioning strategies, and backwards compatibility.

Software ArchitectureAbility to design system architectures that balance scalability, maintainability, reliability, and performance. Experience with architectural patterns and trade-off analysis.

Communication and Technical LeadershipAbility to articulate complex technical concepts clearly to both technical and non-technical stakeholders. Demonstrated ability to influence technical direction through persuasive communication.

Systems DesignExpertise designing distributed systems and platforms. Understanding of consistency models, failure modes, and resilience patterns.

Nice to have

PythonFamiliarity with Python for scripting, automation, and AI/ML tooling integration. Understanding of Python ecosystems for data processing and machine learning.

TypeScriptExperience with TypeScript for building robust JavaScript applications, APIs, or tooling. Understanding of type safety benefits in large codebases.

LLM and AI Agent ArchitectureUnderstanding of large language model capabilities, limitations, and integration patterns. Experience with agent-based systems, multi-step reasoning, and tool use in AI workflows.

DevOps and Infrastructure as CodeExperience with Infrastructure as Code tools like Terraform or CloudFormation. Familiarity with CI/CD pipelines, containerization, and deployment automation.

Developer Experience OptimizationInterest in and experience improving developer experience through thoughtful tool design, clear documentation, and reducing friction in engineering workflows.

Internal Tools and Platform DevelopmentPrior experience building internal platforms, developer tools, or infrastructure products used by large engineering teams.

Vendor CollaborationExperience working closely with technology vendors, providing feedback on beta/early-access products, and influencing product direction.

Observability and MonitoringHands-on experience implementing comprehensive monitoring, distributed tracing, and logging strategies using tools like CloudWatch, Datadog, or similar platforms.

Compensation & benefits

Salary

AUD 160,000 – 220,000 (annual)

Stock options

Available

Benefits

Hybrid Work Flexibility

Work flexibly from anywhere in Australia or New Zealand with hybrid arrangement allowing both remote work and in-person collaboration days. Regular team boost days bring the distributed team together for planning, knowledge sharing, and cross-functional collaboration.

Influence on Strategic Direction

Significant input into the technical direction and roadmap of Xero's AI strategy at the organizational level. Your architectural decisions and technical guidance will shape how thousands of engineers across Xero work with AI technologies.

Early-Access Technology Partnership

Direct collaboration with industry-leading vendors including AWS, Microsoft, and GitHub on beta and early-access AI technologies not yet available in public markets. Unique opportunity to influence the development of emerging tools alongside vendor engineers.

Cross-Functional Team Environment

Work with a close-knit, collaborative team spread across Melbourne, Sydney, and the Sunshine Coast, plus a product manager in Wellington. Genuine collaborative culture that values clear communication and distributed decision-making.

Full End-to-End Ownership

Own projects completely from early experimentation through production operation. Responsibility for runbooks, monitoring, rollback strategies, and operational excellence creates meaningful ownership and impact.

Learning and Development

Access to structured learning resources, conference attendance opportunities, and development budget to stay current with rapidly evolving AI engineering practices and emerging technologies.

Professional Growth Opportunities

Chance to grow as a technical leader, mentor junior engineers, and develop strategic thinking about organizational technical direction. Clear pathway to staff engineer or technical leadership roles within Xero.

Meaningful Impact

Build internal tools and platforms that directly improve productivity for hundreds of engineers across Xero. Your work enables teams to ship faster and better through improved AI capabilities and tooling.

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