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Salary
≈ $67k – $139k per year (Estimated)
Location
Hybrid (Madrid, Spain)
Seniority
Senior · 5+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 27, 2026. First seen by Alion on Sep 2, 2026. DDN scores A on the Alion truth index.

Overview
Company
Impact
Profile match

DDN

DDN (DataDirect Networks) is a data storage company headquartered in Chatsworth, California that builds high-performance storage systems and a data intelligence platform for AI factories, cloud providers and supercomputing. Formed in 1998 through the merger of MegaDrive and ImpactData by co-founders Alex Bouzari and Paul Bloch, it has systems in 48 of the world's top 100 supercomputers and took a $300 million investment from Blackstone at a $5 billion valuation. It hires Rust, Go and Lustre software engineers, DevOps and build engineers, solutions architects, support engineers, manufacturing test technicians, and sales, tax and legal staff.

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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