The DataDirect Networks Principal Solutions Architect role blends deep technical expertise with a strong consultative approach to helping customers build and scale AI, ML, and HPC solutions. This position plays a key role in connecting DDN’s AI and data platform technologies to real customer business challenges — helping organizations improve performance, reduce latency, increase operational efficiency, and accelerate time-to-insight.
Core ResponsibilitiesServe as a trusted advisor to customers by understanding their AI, data, and infrastructure challenges and recommending tailored solutions.
Design scalable AI and data architectures that support long-term growth, performance, and operational efficiency.
Partner closely with Sales, Engineering, Product, and Marketing teams to support customer engagements and influence strategy.
Lead technical presentations, demos, proof-of-concepts, and customer workshops throughout the sales cycle.
Support partner and alliance relationships across cloud providers, OEMs, integrators, and hyperscalers.
Deliver enablement and technical training to internal teams and external partners.
Stay current on AI, data infrastructure, and competitive market trends to effectively position DDN solutions.
Strong background in AI/ML infrastructure, data engineering, AI application development, or technical consulting.
Experience with modern AI technologies including LLMs, RAG, inference, neural networks, vector databases, and AI pipelines.
Hands-on familiarity with tools and frameworks such as TensorFlow, PyTorch, NVIDIA Enterprise Suite, NeMO, and NIMs.
Ability to communicate effectively with both technical teams and executive stakeholders.
Experience supporting complex customer engagements in a pre-sales or solution consulting environment.
Strong presentation, relationship-building, and strategic problem-solving skills.
Bachelor’s degree in Computer Science, AI, Data Engineering, or a related field (or equivalent experience).
Experience working with cloud providers, strategic alliances, and partner ecosystems.
Background in technical sales engineering, AI consulting, or customer-facing architecture roles.
Understanding of AI infrastructure optimization, scalability, and data center performance considerations
Skills Required
- Strong background in AI/ML infrastructure, data engineering, AI application development, or technical consulting
- Experience with LLMs, RAG, inference, neural networks, vector databases, and AI pipelines
- Hands-on familiarity with TensorFlow, PyTorch, NVIDIA Enterprise Suite, NeMo, and NIMs
- Ability to communicate effectively with technical teams and executive stakeholders
- Experience supporting complex customer engagements in a pre-sales or solution consulting environment
- Strong presentation, relationship-building, and strategic problem-solving skills
- Bachelor's degree in Computer Science, AI, Data Engineering, or a related field, or equivalent experience
- Experience working with cloud providers, strategic alliances, and partner ecosystems
- Background in technical sales engineering, AI consulting, or customer-facing architecture roles
- Understanding of AI infrastructure optimization, scalability, and data center performance considerations
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.
