The AI Solution Architect carries deep domain expertise in one or more of the following, paired with strong command of the IFS AI portfolio:
• ERP-centric: Deep understanding of enterprise resource planning processes, market dynamics, and the competitive landscape.
• EAM-centric: Deep understanding of enterprise asset management (EAM), APM, and AIP market dynamics.
• FSM-centric: Deep understanding of field service software market dynamics, including products, competitors, customers, and partners.
• Multi-domain: Several architects will operate credibly across two or more of these disciplines.
• Contribution to AI portfolio revenue targets in partnership with sales leadership.
• Measurable improvement in presales readiness and win rates on qualified opportunities.
• Quality and reuse of solution assets, demonstrations, and proof-of-value engagements.
• Field-sensed product feedback that fuels future AI portfolio innovation.
• Self-Starter and Fast Learner: Thrives in a high-paced, dynamic business environment. Learns quickly and adapts with agility.
• Subject Matter Expertise: Deep domain credibility in ERP, EAM, and/or FSM, combined with genuine fluency in applied AI.
• Strong Team Player: Acts as both player and coach. Builds community, shares knowledge, and mentors rising talent across geographies.
• Presentation and Demonstration Skills: Skilled in delivering both software demonstrations and executive-level presentations, with the ability to tailor delivery to varied audiences.
• Technical Skills: Solid grasp of business and IT architecture; capable of assessing customer technology landscapes in the context of AI-led business transformation.
• Global Readiness: Fluent in English, with additional language skills seen as an advantage. Willingness to travel internationally and work flexible hours to support global engagements is essential.
• Interpersonal Skills: Creative, curious, and persuasive communicator, capable of influencing direction across technical and non-technical stakeholders at all levels.
• AI-first worker: Working “AI-first”, applying AI techniques to become both more efficient in everyday work, and more effective in customer engagements. Naturally curious and continuously finds new approaches and solutions.