Blaize is building a hybrid AI platform engineered to support edge-to-cloud intelligence at scale—delivering efficient, scalable AI designed for complex, multimodal workloads across industries. We serve critical infrastructure sectors including smart city, defense, retail, manufacturing, healthcare, and automotive.

Our full-stack programmable processor architecture and low-code/no-code software platform enable real-time AI processing for high-performance computing at the network’s edge and in the data center. Blaize solutions deliver actionable insights with low power consumption, high efficiency, minimal size, and low cost.Headquartered in El Dorado Hills (CA), Blaize has over 200 employees worldwide, with teams in San Jose (CA) and Cary (NC), and subsidiaries in Hyderabad (India), Leeds and Kings Langley (UK), and Abu Dhabi (UAE).

To learn more, visit www.blaize.com or follow us on LinkedIn at @blaizeinc.

 

We are looking for a technically deep, commercially sharp Solutions Architect to own the technical pre-sales and solution design motion for Blaize's AI infrastructure across data center and enterprise deployments. This is a high-visibility, high-impact role at the intersection of AI silicon, software platforms, and go-to-market — working directly with cloud providers, system integrators, OEM partners, and enterprise customers to architect and evangelize Blaize-powered AI deployments.

You will be the technical face of Blaize in customer engagements, owning everything from initial solution design through POC execution, reference architecture development, and partner enablement.

Key Responsibilities

Technical Pre-Sales & Solution Design

• Design and present AI infrastructure solutions leveraging GPU, CPU, DPU, NPU, and Blaize's software platform for data center and enterprise deployments
• Lead technical discovery, solution scoping, and architecture reviews with cloud providers, system integrators, and enterprise customers
• Own POC execution and drive technical evaluations to successful outcomes

AI Workload Architecture

• Map customer AI workloads — including transformer and CNN-based models — onto Blaize and complementary hardware/software stacks
• Demonstrate total cost of ownership (TCO) advantages of Blaize architectures, including hybrid GPU/Blaize configurations in data center environments
• Translate complex workload requirements into concrete, deployable architectures

Cloud & Hybrid Integration

• Architect production deployments of Blaize's AI Services Platform for cloud providers, system integrators, and enterprises
• Enable customers to deploy business-outcome applications without building the underlying AI stack from scratch
• Evangelize Blaize's hybrid edge-to-cloud approach across both hardware and software layers

Go-to-Market Enablement

• Develop reference architectures, whitepapers, and technical collateral that accelerate customer adoption
• Serve as a trusted technical advisor to data center and enterprise customers and their integration partners
• Support the sales team with technical positioning, competitive differentiation, and deal strategy

Ecosystem & Partner Development

• Collaborate with OEM and channel partners to scale co-branded AI edge data center deployments globally
• Build and maintain strong technical relationships across the cloud and SI partner ecosystem
• Represent Blaize at industry events, conferences, and partner summits

Cross-functional Leadership

• Bridge product, engineering, and sales to ensure the Blaize platform roadmap reflects real customer and market needs
• Provide structured field feedback to influence product prioritization and roadmap decisions
• Mentor and support junior members of the solutions and pre-sales team

Qualifications

• 8–12 years of experience in solutions architecture, pre-sales engineering, or AI infrastructure roles
• Deep technical understanding of AI acceleration technologies — GPU, CPU, DPU, NPU — and data center deployment architectures
• Hands-on experience with AI/ML frameworks and workload types including transformer and CNN-based models
• Experience working with cloud providers (AWS, Azure, GCP) and/or system integrators in a technical capacity
• Proven ability to lead customer-facing POCs and translate technical value into business outcomes
• Strong communication and presentation skills — equally comfortable in a whiteboard session with engineers and a business review with executives
• Experience with edge AI, hybrid cloud architectures, or AI inference platforms is a strong plus
• Bachelor's degree in Computer Science, Electrical Engineering, or a related technical field; advanced degree preferred

Leadership Profile

• Entrepreneurial and self-directed — comfortable operating with ambiguity in a fast-moving environment
• Customer-obsessed with strong commercial instincts
• Collaborative across engineering, product, and sales without being slowed down by org boundaries
• Credible, confident technical communicator who earns trust quickly