Senior Sales Engineer - Strategic AI
- Role
- Sales
- Experience
- Senior
- Employment
- Full-time
Open to FR only. Set where you work from to check your eligibility.
No BS summary
Senior sales engineer in France for storage and AI infrastructure solutions. Needs 3+ years in pre-sales, solutions architecture, or technical consulting, with enterprise storage and customer-facing technical sales experience.
Core skills
Required skills
Optional skills
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
What you'll do
- Partner with customers to understand critical data challenges such as 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
- Architect storage for AI/ML training, HPC simulations, data analytics, and GPU-accelerated workloads
- Design for reliability, resilience, security, and scale while 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
- 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 they require
- 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 such as Lustre, GPFS, and Exascaler
- Aptitude for AI workloads and how storage enables AI innovation
- Ability to communicate technical concepts to both engineers and executives
- 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
- 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
- Preferred: Experience with AI/ML infrastructure, HPC, or high-performance workloads
- Success managing complex technical sales cycles
- Genuine curiosity about AI and its impact across industries
- Ownership mindset and persistence in solving problems
- Ability to translate technical complexity into business value
- Ability to thrive in fast-evolving technology environments
- Collaborative team player with integrity and empathy
DDN is positioned as NVIDIA’s storage and data intelligence partner for AI factories and the NVIDIA AI Data Platform.