AI Value Engineer, EMEA

About the role

The AI Value Engineer, EMEA, helps enterprise customers quantify and communicate the business value of DDN's AI and data infrastructure solutions. As part of DDN's global Go to Market Centre of Excellence, the role supports strategic customer opportunities while developing reusable value frameworks, tools and methodologies for Sales and Solution Engineering teams worldwide. It sits at the intersection of AI, technology, strategy and commercial value.

Key responsibilities

• Lead AI value discovery workshops with enterprise customers and prospects, understanding their AI strategies, use cases, workloads and infrastructure challenges.
• Build compelling ROI, TCO and business case models for AI and data infrastructure investments, quantifying impacts such as productivity, utilization, performance, scalability, operational efficiency and time-to-value.
• Develop AI-specific value frameworks, methodologies and tools that can be reused across customers, industries and sales cycles.
• Help customers understand the economics of AI, from experimentation and proof-of-concept through to production-scale deployment.
• Partner with Product Marketing and Product teams on AI value messaging, customer proof points and success metrics.
• Build and maintain benchmarks, market intelligence and competitive insights on AI infrastructure and economics.
• Help establish and scale DDN's AI Value Engineering Centre of Excellence.

Required profile

• 5+ years of experience in Value Engineering, Management Consulting, Strategy, Solutions Consulting, Sales Engineering or a similar customer-facing role.
• Bachelor's degree in Business, Economics, Engineering, Computer Science or a related discipline.
• Fluent English; additional European languages are a plus.

Required skills

• Experience building ROI, TCO and financial models, and investment business cases.
• Strong analytical skills and excellent presentation skills with senior executives.
• Preferred: understanding of AI/ML workloads and their infrastructure, and experience with enterprise AI strategy and investment decisions.