Sales Engineer - LATAM

Data Direct Networks

1d•Remote

About The Position

This is an incredible opportunity to be part of a company that has been at the forefront of AI and high-performance data storage innovation for over two decades. DataDirect Networks (DDN) is a global market leader renowned for powering many of the world's most demanding AI data centers, in industries ranging from life sciences and healthcare to financial services, autonomous cars, Government, academia, research and manufacturing. "DDN's A3I solutions are transforming the landscape of AI infrastructure." – IDC “The real differentiator is DDN. I never hesitate to recommend DDN. DDN is the de facto name for AI Storage in high performance environments” - Marc Hamilton, VP, Solutions Architecture & Engineering | NVIDIA DDN is the global leader in AI and multi-cloud data management at scale. Our cutting-edge data intelligence platform is designed to accelerate AI workloads, enabling organizations to extract maximum value from their data. With a proven track record of performance, reliability, and scalability, DDN empowers businesses to tackle the most challenging AI and data-intensive workloads with confidence. Our success is driven by our unwavering commitment to innovation, customer-centricity, and a team of passionate professionals who bring their expertise and dedication to every project. This is a chance to make a significant impact at a company that is shaping the future of AI and data management. Our commitment to innovation, customer success, and market leadership makes this an exciting and rewarding role for a driven professional looking to make a lasting impact in the world of AI and data storage. 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.

Requirements

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
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

Nice To Haves

Experience with AI/ML infrastructure, HPC, or high-performance workloads (preferred)
Success managing complex technical sales cycles
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

Responsibilities

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
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
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