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Job description
Implementation Consultant – AI Service ApplicationsWe are looking for a hybrid technical and functional specialist to lead the implementation and ongoing management of our new AI Technician Assist platform. The platform analyzes historical service data, repair patterns, failure codes, and OEM resources to help field and shop technicians reach a faster, more accurate diagnosis of a customer-reported machine failure.The role sits at the intersection of AI technology, our e-Emphasys ERP service data, and real-world equipment service operations. The ideal candidate can speak credibly with an AI product team, read our ERP service data structures, and just as importantly, understand how a technician actually works through a failure in the field.Solution Implementation: Lead the end-to-end implementation of the AI Technician Assist platform, covering configuration, data integration, pilot rollout, and scaling across service centers, partnering with IT, Service Operations, and the e-Emphasys ERP Product team.ERP & Data Integration: Own the integration between the AI Assist platform and the e-Emphasys ERP Service module (service orders, machine/unit history, warranty, parts, labor, and task codes) so the platform can pull accurate repair and failure history for root-cause analysis.AI Performance & Feedback: Partner with the data science/AI Product team to define success criteria, validate model output against actual repair outcomes, and run a standing feedback loop from dealer technicians back to Product engineering.Technician Workflow Design: Translate real-world troubleshooting workflows (symptom, diagnostic steps, root cause, repair) into the platform's guided assist flows.Change Management & Training: Develop training materials and SOPs, run pilot programs, and drive adoption across a technician workforce with varying levels of digital comfort.Stakeholder Communication: Report progress, risks, and adoption metrics to Service Operations leadership, IT, and the Product team.Technical / AI & ERP3+ years of hands-on experience with AI/ML-enabled applications, including how recommendation, natural language, or diagnostic/decision-support models are built, trained, and evaluated. A data science background is not required, but the candidate must be conversant with AI capabilities, limitations, and data requirements.Working knowledge of a heavy equipment dealer ERP (e-Emphasys, Infor, or SAP), specifically the Service module, and how that data can be extracted or integrated via APIs.Experience with system integration concepts (APIs, data pipelines, middleware) sufficient to read data models and troubleshoot integration issues alongside developers. Production coding is not required.Familiarity with data quality and governance practices, ensuring the historical service data feeding the AI model is clean, complete, and properly mapped.Functional / Service & Technician PerspectiveSolid functional understanding of heavy equipment dealer operations from a Service and Parts perspective, including service order lifecycle, warranty claims, technician dispatch, and shop/field service workflows.Direct familiarity with how field and shop technicians diagnose equipment failures, including troubleshooting logic, use of OEM manuals and bulletins, and common root-cause categories (mechanical, electrical, hydraulic).Education & ExperienceBachelor's degree in a related field (Computer Science, Information Systems, Engineering, or equivalent practical experience), or equivalent combination of education and hands-on service/technology experience.5+ years of combined experience across ERP/service systems, technology implementation, and/or heavy equipment service operations.Preferred QualificationsPrior experience at a heavy equipment dealer, OEM, or industrial service organization (construction, agriculture, mining, or drilling equipment).Experience working directly with an AI/software vendor on a pilot-to-scale product rollout.Prior experience with service technology rollouts such as mobile service apps, diagnostic tools, or telematics.Familiarity with change management frameworks for technology adoption among a frontline, non-desk workforce.What Success Looks LikeSuccessful pilot and phased rollout of the AI Technician Assist platform across targeted service centers, on schedule.Measurable improvement in diagnostic accuracy and reduction in average diagnostic/repair time for participating technicians.Improved first-time-fix rate and reduction in repeat visits for the same complaint.Technician adoption and satisfaction, meaning the tool is actively used and trusted in the field, not bypassed.Clean, well-integrated data pipeline between the e-Emphasys ERP and the AI platform, with minimal manual data wrangling.
Worksite address
cary, NC, 27511, US
Who can apply
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