Senior Sales Engineer - Strategic AI

Posted Yesterday
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Office, Lilongwe, Central Region, MWI
In-Office
Senior level
Artificial Intelligence • Machine Learning • Software • Analytics
The Role
Architect storage and infrastructure solutions for AI/ML, HPC, analytics, trading, genomics, and autonomous systems. Engage customers, translate technical requirements, develop architectures, BOMs, proposals, demonstrations, proofs of concept, and benchmarks, and guide complex technical sales cycles. Collaborate with Product and Engineering, provide technical thought leadership, mentor team members, and shape product direction. The role requires expertise in storage architectures, networking protocols, reliability, scalability, security, and customer-facing solution design.
Summary Generated by Built In

As a Advisory Solution 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 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 BringTechnical 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

Skills Required

  • Strong understanding of storage and data architectures, including SAN, NAS, object storage, and parallel file systems
  • Knowledge of architectural patterns for reliability, resilience, security, and scale
  • Understanding of storage and data protocols including S3, POSIX, NFS, and SMB
  • Familiarity with TCP/IP, InfiniBand, and RDMA network protocols
  • 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 engineers and executives
  • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience
  • Strong analytical and problem-solving skills
  • Customer-facing communication skills
  • Three to eight or more years of experience in pre-sales, solutions architecture, or technical consulting
  • Proven track record designing storage or infrastructure solutions
  • Hands-on experience with enterprise storage systems
  • Experience managing complex technical sales cycles
  • Experience with AI/ML infrastructure, HPC, or high-performance workloads
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The Company
HQ: Chatsworth, CA
706 Employees
Year Founded: 1998

What We Do

DDN is the world’s largest private data storage company and the leading provider of intelligent technology and infrastructure solutions for Enterprise At Scale, AI and analytics, HPC, government and academia customers. Through its DDN and Tintri divisions, the company delivers AI, Data Management software and hardware solutions, and unified analytics frameworks to solve complex business challenges for data-intensive, global organizations. DDN provides its enterprise customers with the most flexible, efficient and reliable data storage solutions for on-premises and multi-cloud environments at any scale. Over the last two decades, DDN has established itself as the data management provider of choice for over 11,000 enterprises, government, and public-sector customers, including many of the world’s leading financial services firms, life science organizations, manufacturing and energy companies, research facilities, and web and cloud service providers.

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