Principal Solutions Architect - FSI

DDN; New York (NY); Hybrid; USD 180,000 - 240,000; Full time

Job summary

DDN is seeking a Principal Solutions Architect to blend deep technical expertise with a consultative approach, helping customers build and scale AI, ML, and HPC solutions in New York.

You will design scalable AI and data architectures, collaborate with Sales, Engineering, and Product teams, lead technical demonstrations and workshops, and help position DDN's AI platform to drive performance and time-to-insight for customers.

Qualifications

• Strong background in AI/ML infrastructure, data engineering, 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 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.

Responsibilities

• Serve as trusted advisor to customers on AI, data, and infrastructure challenges.
• Design scalable AI and data architectures for long-term growth and performance.
• Collaborate with Sales, Engineering, Product, and Marketing to support engagements.
• Lead technical presentations, demos, PoCs, and workshops throughout the sales cycle.
• Support partner and alliance relationships across cloud providers, OEMs, integrators, and hyperscalers.
• Deliver enablement and training to internal teams and external partners.
• Stay current on AI, data infrastructure, and competitive market trends to position DDN solutions.

Skills

AI/ML infra

Data engineering

Technical consulting

Pre-sales

Presentation/communication

Education

Bachelor’s degree

Tools

TensorFlow

PyTorch

NVIDIA Enterprise Suite

NeMO

NIMs

Job description

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

• Serve 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.

What We’re Looking For

• 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.

Preferred Background

• 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