Senior Sales Engineer - Strategic AI
DDN · Paris, Ile-de-France, France
Software Development · 1,001-5,000 employees
About the role
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.
What they look for
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 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
