AI Platform Engineer

Wexford, IrelandHybrid3 days ago

Job description

Scurri is seeking a self-driven AI Platform Engineer to lead the design, delivery, and adoption of AI-powered automations across Scurri. Reporting to the COO, you will work cross-departmentally to identify opportunities for automation and build solutions using modern AI models and workflow platforms. This role goes beyond simply shipping automations: for every project, you will work alongside the people who will own it day-to-day, so that once a solution is live, the department itself is equipped to maintain and extend it, with you available for escalations rather than routine maintenance. ## Key Responsibilities - Partner directly with stakeholders across departments to scope vague, real-world problems into concrete, actionable automation projects. - Have the skills and ability to map “as is” workflows into business process maps and to create “to be” automation solutions and technical schemas to gain buy-in from relevant business process owners. - Design, build, and deploy end-to-end automation workflows and AI-powered agents, using platforms such as n8n, Zapier, and Make alongside custom backend services. - Integrate large language models (Claude, Gemini, OpenAI, or similar) into internal workflows to support tasks such as classification, summarisation, document processing, and decision support. - Embedded with each department for the duration of a project, working with the people involved rather than working for them, so they build the skills to run and adapt what's delivered. - Document workflows and playbooks, and run hands-on enablement sessions so departmental teams become self-sufficient owners of their own automations. - Establish a clear escalation path for automations that have been handed over, stepping back in only when an issue is beyond the owning team's ability to resolve. - Manage your own project pipeline and priorities across multiple departments at once, balancing new builds, in-flight enablement, and escalation support. - Monitor the performance, cost, and reliability of deployed automations and agents, iterating on model selection, prompt design, and error handling. - Champion security and data-handling best practices across all automations, particularly where third-party AI providers and sensitive data are involved. - Stay up to date with developments in the AI and automation space, evaluating new tools, frameworks, and providers for potential adoption. - Feed reusable patterns, components, and learnings back into a shared knowledge base to accelerate future AI enablement work across the company. …