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AI Value Engineer

📅 Sep 2
Value EngineeringROI ModelingTCO ModelingFinancial Modeling
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📜 Description

  • Lead AI value discovery workshops with enterprise customers and prospects.
  • Translate customer AI strategies, workloads, and infrastructure challenges into measurable business outcomes.
  • Build ROI, TCO, and business case models for AI and data infrastructure investments.
  • Develop reusable AI value frameworks, methodologies, and tools for customer engagements and sales teams.
  • Partner with Product Marketing and Product teams on value messaging, proof points, and success metrics.
  • Maintain AI infrastructure benchmarks, market intelligence, and competitive insights.

🛠️ Requirements

  • 5+ years of experience in Value Engineering, Management Consulting, Strategy, Solutions Consulting, Sales Engineering, or a similar customer-facing role.
  • Experience building ROI, TCO, financial models, and investment business cases.
  • Strong analytical skills, with the ability to turn complex data into a clear commercial story.
  • Excellent presentation and communication skills, particularly with senior executives.
  • Comfortable working across long, complex enterprise sales cycles and multiple stakeholders.
  • Ability to work across multiple countries and cultures in a fast-moving environment.
  • Bachelor’s degree in Business, Economics, Engineering, Computer Science, or a related discipline.
  • Understanding of AI/ML workloads and the infrastructure required to support them.
  • Experience working with enterprise customers on AI strategy, transformation, or technology investment decisions.
  • Fluent English; additional European language skills are a plus.
Full job description

AI Value Engineer, EMEA

About the Role
The AI Value Engineer, EMEA, will help 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, you will support strategic customer opportunities while developing reusable value frameworks, tools, and methodologies for Sales and Solution Engineering teams worldwide.

You will operate at the intersection of AI, technology, strategy, and commercial value—translating complex infrastructure decisions into compelling demonstrations, measurable outcomes, and clear investment cases for both technical and C-level audiences.

Key Focus Areas

  • Demo Excellence: Enhancing how DDN presents its technology and customer value during sales engagements.

  • Scalable Value Engineering: Creating repeatable frameworks and tools for value discovery, ROI, TCO, and business case development.

  • Field Enablement: Helping customer-facing teams and partners use value engineering assets confidently and effectively.

  • Commercial Impact: Supporting strategic opportunities and measuring how CoE initiatives contribute to customer outcomes, pipeline progression, and revenue.

Responsibilities

  • Lead AI value discovery workshops with enterprise customers and prospects.

  • Understand customer AI strategies, use cases, workloads, and infrastructure challenges, translating them into measurable business outcomes.

  • Build compelling ROI, TCO, and business case models for AI and data infrastructure investments.

  • Quantify the financial impact of AI infrastructure decisions, including improvements in 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 to develop AI value messaging, customer proof points, and success metrics.

  • Build and maintain benchmarks, market intelligence, and competitive insights relating to AI infrastructure and economics.

  • Help establish and scale DDN’s AI Value Engineering Centre of Excellence.

Qualifications

  • 5+ years of experience in Value Engineering, Management Consulting, Strategy, Solutions Consulting, Sales Engineering, or a similar customer-facing role.

  • Experience building ROI, TCO, financial models, and investment business cases.

  • Strong analytical skills, with the ability to turn complex data into a clear commercial story.

  • Excellent presentation and communication skills, particularly with senior executives.

  • Comfortable working across long, complex enterprise sales cycles and multiple stakeholders.

  • Ability to work across multiple countries and cultures in a fast-moving environment.

  • Bachelor’s degree in Business, Economics, Engineering, Computer Science, or a related discipline.

Preferred Qualifications

  • Understanding of AI/ML workloads and the infrastructure required to support them.

  • Experience working with enterprise customers on AI strategy, transformation, or technology investment decisions.

  • Fluent English; additional European language skills are a plus.

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