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Full-time
bachelor degree
Posted 27d ago
~40 hrs/week
Remote in France
Responsibilities
You will architect high-performance storage solutions for AI, HPC, and data-intensive workloads while serving as a trusted technical advisor throughout the sales cycle. Responsibilities include conducting POCs, designing system architectures, and collaborating with product teams to shape future technology.
Requirements
Candidates should have 3-8+ years of experience in pre-sales or solutions architecture with a strong foundation in storage protocols and data architectures. A bachelor's degree in Computer Science or Engineering is required, along with the ability to communicate complex technical concepts to both engineers and executives.
Full job description
As a Sales Engineer, you'll architect high-performance storage solutions that enable customers to achieve their boldest ambitions. Work across finance, pharmaceuticals, education, and physical AI—designing systems that power real-time trading, accelerate drug discovery, enable groundbreaking research, and fuel autonomous systems.
You'll translate complex customer requirements into elegant technical solutions, demonstrate capabilities through POCs and benchmarks, and serve as a trusted advisor throughout the sales cycle.
What You'll Do
Customer Engagement
Partner with customers to understand their critical data challenges—high-frequency trading, genomics processing, AI model training, or autonomous vehicle sensor fusion
Translate technical requirements into elegant, scalable storage solutions that exceed expectations
Act as trusted technical advisor throughout the sales cycle
Solution Design
Architect storage for AI/ML training, HPC simulations, data analytics, and GPU-accelerated workloads
Design for reliability, resilience, security, and scale—balancing performance with data protection
Create BOMs, system architectures, and technical proposals for complex RFPs
Conduct live demos, POCs, and performance benchmarking
Integrate with GPU clusters, Kubernetes, cloud platforms, and AI frameworks
Innovation & Growth
Stay current on AI infrastructure and storage technology trends
Collaborate with Product and Engineering teams using field insights
Mentor team members and contribute to technical thought leadership
Shape product direction based on customer needs
What You Bring
Technical Foundation (All Levels)
Strong understanding of storage and data architectures: SAN, NAS, object storage, parallel file systems
Knowledge of architectural patterns for reliability, resilience, security, and scale
Understanding of storage and data protocols: S3, POSIX, NFS, SMB
Familiarity with network protocols: TCP/IP, InfiniBand, RDMA
Curiosity about massively parallel technologies (Lustre, GPFS, Exascaler)
Aptitude for AI workloads and how storage enables AI innovation
Ability to communicate technical concepts to both engineers and executives
Entry Level (0-3 years)
Bachelor's in Computer Science, Engineering, or related field (or equivalent experience)
Exposure to storage/systems through coursework, internships, or projects
Strong analytical and problem-solving skills
Customer-facing communication skills
Experienced (3+ years)
3-8+ years in pre-sales, solutions architecture, or technical consulting
Proven track record designing storage/infrastructure solutions
Hands-on experience with enterprise storage systems
Experience with AI/ML infrastructure, HPC, or high-performance workloads (preferred)
Success managing complex technical sales cycles
What Sets You Apart
Genuine curiosity about AI and its impact across industries
Ownership mindset—you solve problems until they're solved
Ability to translate technical complexity into business value
Thrive in fast-evolving technology environments
Collaborative team player with integrity and empathy
The Global Leader in AI and Data Intelligence Solutions.
Industry
Software Development
Company size
1,001-5,000 employees
Headquarters
Chatsworth, CA
LinkedIn followers
93,947
DDN is the world’s leading AI and data intelligence company, powering the world’s most demanding AI workloads by keeping GPUs fed, efficient, and productive—at massive scale—so organizations can train, checkpoint, and infer faster with less footprint and power while achieving tremendous ROI from their AI investments. From hyperscalers and next-gen cloud builders to enterprises, governments, and research institutions, DDN delivers proven data intelligence at exabyte scale across hundreds of thousands of GPUs—so customers can deploy AI with confidence, accelerate time-to-value, and realize outsized returns.
Offices: 9351 Deering Avenue, Chatsworth, CA 91311, US · 10 Eagle St, Brisbane City, Queensland 4000, AU · 9950 Federal Dr, Ste 150, Colorado Springs, Colorado 80921, US · 4850 Ward Rd, 101, Wheat Ridge, Colorado 80033, US · 8320 Guilford Rd, Suites D/E, Columbia, Maryland 21046, US
Artificial IntelligenceData StorageMachine LearningAnalyticsEnterprise AIHigh-Performance ComputingGenomicsSecurityData ScienceGenerative AI
The Global Leader in AI and Data Intelligence Solutions.
Industry
Software Development
Company size
1,001-5,000 employees
Headquarters
Chatsworth, CA
LinkedIn followers
93,947
DDN is the world’s leading AI and data intelligence company, powering the world’s most demanding AI workloads by keeping GPUs fed, efficient, and productive—at massive scale—so organizations can train, checkpoint, and infer faster with less footprint and power while achieving tremendous ROI from their AI investments. From hyperscalers and next-gen cloud builders to enterprises, governments, and research institutions, DDN delivers proven data intelligence at exabyte scale across hundreds of thousands of GPUs—so customers can deploy AI with confidence, accelerate time-to-value, and realize outsized returns.
Offices: 9351 Deering Avenue, Chatsworth, CA 91311, US · 10 Eagle St, Brisbane City, Queensland 4000, AU · 9950 Federal Dr, Ste 150, Colorado Springs, Colorado 80921, US · 4850 Ward Rd, 101, Wheat Ridge, Colorado 80033, US · 8320 Guilford Rd, Suites D/E, Columbia, Maryland 21046, US
Artificial IntelligenceData StorageMachine LearningAnalyticsEnterprise AIHigh-Performance ComputingGenomicsSecurityData ScienceGenerative AI