Senior Engineer - AI Workflows
Explicitly requires vibe-coding; fast experimentation building agentic AI workflows and integrations.
About the Role
Senior Engineer on Xero's Internal AI Accelerator Squad to design, build, and operationalise agentic AI workflows and integrations across internal business teams. Lead delivery of AI agents from discovery to production while defining patterns, guardrails, and tooling to enable safe, scalable intelligent automation.
Job Description
Role
As a Senior Engineer on the Internal AI Accelerator Squad, you will embed with internal business teams to co-design and operationalise agentic AI workflows. You will lead delivery of high-stakes AI agents from discovery to production and define patterns, guardrails, and tooling to enable safe, scalable intelligent automation.
Team
Join a high-velocity squad focused on boosting adoption of agentic AI and intelligent automation across the global business. The team emphasizes rapid experimentation and βvibe-coding,β collaborating closely with product owners and subject matter experts to convert complex workflows into automated solutions.
Key Responsibilities
- Design and iterate on AI agents and workflow orchestrations using models and platforms such as Claude, Gemini, and MCP.
- Integrate AI systems with core enterprise platforms, including Salesforce, Workday, Slack, and NetSuite.
- Develop reusable automation patterns and shared templates for business adoption.
- Build evaluation and monitoring frameworks to measure performance and ensure safety and auditability of AI-native workflows.
- Partner with non-technical stakeholders to translate business pain points into technical designs and deliver production-ready solutions.
- Act as a technical evangelist and coach to raise AI fluency across teams.
Requirements
- Significant experience building and operating applications or automations in production, especially involving APIs and cloud infrastructure.
- Hands-on delivery experience with AI-driven solutions such as agents, copilots, or RAG systems using LLMs (examples cited: Claude, Gemini).
- Proficiency in programming with Python or TypeScript and familiarity with SDKs and webhooks.
- Systems-thinking approach with a focus on security, auditability, and limiting blast radius.
- Strong stakeholder collaboration and communication skills; experience coaching and facilitating workshops.
Where and how you can work
- Hybrid working model: autonomy to work from home with regular in-office βboostβ days for collaboration in modern office spaces.