Senior Sales Engineer
At a glance
Senior Solutions & Sales Engineering role at DDN. Santa Clara · full-time · $250,000–$300,000 base.
Growth Roles summary, based on the employer's posting.
What you'll do
- Work with customers on storage challenges involving trading, genomics, AI training, or vehicle sensor data
- Turn technical needs into scalable storage designs for AI, HPC, analytics, and GPU workloads
- Prepare bills of materials, system architectures, and proposals for complex RFPs
- Run demonstrations, proofs of concept, and performance tests, including integrations with Kubernetes and cloud platforms
- Guide technical sales cycles while feeding customer insights into product direction and mentoring teammates
What you bring
- At least three years in pre-sales, solutions architecture, or technical consulting
- A record of designing storage or infrastructure solutions with hands-on enterprise storage experience
- Working knowledge of SAN, NAS, object storage, parallel file systems, and protocols including S3, POSIX, NFS, and SMB
- Familiarity with TCP/IP, InfiniBand, and RDMA, plus an understanding of reliability, security, resilience, and scale
- You can explain technical systems clearly to both engineers and executives
Who this fits
You’ll suit a senior, customer-facing technical role if you combine storage depth with experience guiding complex sales cycles. The work spans AI infrastructure, HPC, analytics, GPU clusters, Kubernetes, cloud platforms, and high-performance workloads. This is a hybrid position in Santa Clara, with stated annual pay of $250,000 to $300,000.
From the employer
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)
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
Diverse Backgrounds Welcome: Whether you're coming from enterprise storage vendors (Weka, VAST, NetApp, Pure), research computing (university HPC, national labs), or infrastructure roles (cloud architects, 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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