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Senior Sales Engineer

📅 Sep 15
Sales EngineeringPre-salesSolutions ArchitectureEnterprise Storage
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📜 Description

  • Partner with customers to understand data and infrastructure challenges.
  • Translate technical requirements into scalable storage solutions and advise customers throughout the sales cycle.
  • Architect storage for AI/ML training, HPC simulations, analytics, and GPU-accelerated workloads.
  • Design systems for performance, reliability, resilience, security, and data protection.
  • Create system architectures, bills of materials, and technical proposals for complex RFPs.
  • Conduct demonstrations, proofs of concept, and performance benchmarks; integrate solutions with GPU clusters, Kubernetes, cloud platforms, and AI frameworks.

🛠️ Requirements

  • 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

✨ Benefits

  • Flexible work arrangements
  • Industries We Serve
  • Financial Services: High-frequency trading, risk modeling, real-time analytics
  • Pharmaceuticals: Genomics sequencing, drug discovery, clinical research
  • Education & Research: University HPC, AI research, climate modeling, scientific computing
  • Physical AI & Robotics: Autonomous vehicles, robotic systems, sensor data processing
Full job description

About DDN

DDN powers the world's most demanding data workloads—from AI research to drug discovery, autonomous vehicles to financial modeling. For over two decades, our massively parallel storage solutions have enabled breakthrough innovations across industries. Join us in building the infrastructure that makes the impossible possible.

The Role

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)

  • Experience with parallel technologies (Lustre, GPFS, Exascaler)

  • Strong understanding of storage and data architectures: SAN, NAS, object storage, parallel file systems

  • Knowledge of Storage 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

  • Aptitude for AI workloads and how storage enables AI innovation

  • Ability to communicate technical concepts to both engineers and executives

  • Strong analytical and problem-solving skills

  • Customer-facing communication skills

Experienced (8+ years)

  • 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

Diverse Backgrounds Welcome: Whether you're coming from enterprise storage vendors, research computing, or infrastructure roles (cloud architects, storage Administrator, platform engineers), your experience translates to this role. Technical depth + customer focus matter more than your starting point.

Why DDN

Impact

  • Power cancer research, autonomous vehicles, and AI breakthroughs

  • Work on infrastructure enabling discoveries that change the world

  • See direct results from your designs

Growth

  • Master AI infrastructure, parallel computing, and next-gen storage

  • Learn from world-class engineers and architects

  • Clear career progression: SE → Senior SE → Principal Architect

  • Continuous learning: training, certifications, conferences

Team & Culture

  • 20+ years leading storage innovation

  • Technical excellence and customer obsession

  • Competitive compensation: base, bonuses, stock options, benefits

  • Flexible work arrangements

Industries We Serve

  • Financial Services: High-frequency trading, risk modeling, real-time analytics

  • Pharmaceuticals: Genomics sequencing, drug discovery, clinical research

  • Education & Research: University HPC, AI research, climate modeling, scientific computing

  • Physical AI & Robotics: Autonomous vehicles, robotic systems, sensor data processing

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