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 Responsibilities
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Serve as a trusted advisor to customers by understanding their AI, data, and infrastructure challenges and recommending tailored solutions.
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Design scalable AI and data architectures that support long-term growth, performance, and operational efficiency.
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Partner closely with Sales, Engineering, Product, and Marketing teams to support customer engagements and influence strategy.
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Lead technical presentations, demos, proof-of-concepts, and customer workshops throughout the sales cycle.
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Support partner and alliance relationships across cloud providers, OEMs, integrators, and hyperscalers.
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Deliver enablement and technical training to internal teams and external partners.
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Stay current on AI, data infrastructure, and competitive market trends to effectively position DDN solutions.
What We’re Looking For
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Strong background in AI/ML infrastructure, data engineering, AI application development, or technical consulting.
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Experience with modern AI technologies including LLMs, RAG, inference, neural networks, vector databases, and AI pipelines.
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Hands-on familiarity with tools and frameworks such as TensorFlow, PyTorch, NVIDIA Enterprise Suite, NeMO, and NIMs.
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Ability to communicate effectively with both technical teams and executive stakeholders.
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Experience supporting complex customer engagements in a pre-sales or solution consulting environment.
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Strong presentation, relationship-building, and strategic problem-solving skills.
Preferred Background
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Bachelor’s degree in Computer Science, AI, Data Engineering, or a related field (or equivalent experience).
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Experience working with cloud providers, strategic alliances, and partner ecosystems.
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Background in technical sales engineering, AI consulting, or customer-facing architecture roles.
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Understanding of AI infrastructure optimization, scalability, and data center performance considerations
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