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 DoCustomer EngagementPartner with customers to understand their critical data challenges—high-frequency trading, genomics processing, AI model training, or autonomous vehicle sensor fusionTranslate technical requirements into elegant, scalable storage solutions that exceed expectationsAct as trusted technical advisor throughout the sales cycleSolution DesignArchitect storage for AI/ML training, HPC simulations, data analytics, and GPU-accelerated workloadsDesign for reliability, resilience, security,



and scale—balancing performance with data protectionCreate BOMs, system architectures, and technical proposals for complex RFPsConduct live demos, POCs, and performance benchmarkingIntegrate with GPU clusters, Kubernetes, cloud platforms, and AI frameworksInnovation & GrowthStay current on AI infrastructure and storage technology trendsCollaborate with Product and Engineering teams using field insightsMentor team members and contribute to technical thought leadershipShape product direction based on customer needsWhat You BringTechnical Foundation (All Levels)Strong understanding of storage and data architectures: SAN, NAS, object storage, parallel file systemsKnowledge of architectural patterns for reliability, resilience, security, and scaleUnderstanding of storage and data protocols: S3, POSIX, NFS, SMBFamiliarity with network protocols: TCP/IP, InfiniBand, RDMACuriosity about massively parallel technologies (Lustre, GPFS, Exascaler)Aptitude

📌 Senior Sales Engineer (Madrid)
🏢 DDN
📍 Madrid