FuriosaAI
AI
SolutionsArchitect
Neural analysis suggests this role is
optimal for Mid candidates.
“Solutions Architect at FuriosaAI. Skills: AI/LLM model deployments, RNGD chips/servers, inference frameworks, serving stack evolution, modern inference stacks, agent and orchestration frameworks, DNN frameworks. Own end-to-end technical enablement for US customers deploying AI models on FuriosaAI's RNGD NPU using the Furiosa SDK. Develop POCs, benchmarking studies, and live debugging sessions directly in customer environments”
What You'll Achieve.
bring the full potential of our powerful RNGD chips/servers to our customers; empowering customers with FuriosaAI’s powerful solutions; translate deep technical capability into business value
Industry & Context.
able to travel to customer sites and to Seoul HQ periodically
What They're Looking For.
Must Have
2–5 years in a US customer-facing technical role: Solutions Architect, Sales Engineer, Forward Deployed Engineer, or equivalent at an AI infra, cloud, or semiconductor company, Actively current on the AI/LLM landscape — tracking model releases, inference frameworks, and serving stack evolution in real time, Hands-on experience with modern inference stacks: vLLM, SGLang, TensorRT-LLM, Triton Inference Server, or similar, Hands-on experience with agent and orchestration frameworks: LangChain, LlamaIndex, LangGraph, AutoGen, or MCP-based tooling, Proficiency in comfortable with DNN frameworks (PyTorch, TensorFlow), written and verbal communication — able to engage credibly with ML engineers at frontier labs and VP/C-suite executives, Authorized to work in the able to travel to customer sites and to Seoul HQ periodically
Nice to Have
Prior experience at a US AI chip company, cloud silicon team, or AI infrastructure startup, Familiarity with NPU/GPU accelerator ecosystems, PCIe integration, and data center hardware deployment, Experience with inference optimization: quantization, kernel tuning, batching strategies, memory bandwidth optimization, Proficiency in C, C++, or Rust, Experience working with distributed or cross-timezone engineering teams
What You'll Do.
Own end-to-end technical enablement for US customers deploying AI models on FuriosaAI's RNGD NPU using the Furiosa SDK
and live debugging sessions directly in customer environments
Act as the technical authority to the US BD/Sales team during pre-sales and enterprise
current expertise in FuriosaAI's hardware and software stack and demonstrate it at US technical forums
and customer workshops
Onboard and train customers on integration patterns
optimization workflows
and best practices post-purchase
Serve as a technical feedback loop from US customers back to Seoul HQ product and engineering teams
How You'll Work.
Team & Collaboration
Act as the technical authority to the US BD/Sales team; Serve as a technical feedback loop from US customers back to Seoul HQ product and engineering teams; Experience working with distributed or cross-timezone engineering teams
Communication Scope
written and verbal communication
Full Job Description
ABOUT THE JOB FuriosaAI is looking for a Solutions Architect to bring the full potential of our powerful RNGD chips/servers to our customers by acting as the primary technical authority in AI/LLM model deployments. From running POCs to benchmarking and debugging, you will translate RNGD’s powerful system to real-world deployments of customers’ models, empowering customers with FuriosaAI’s powerful solutions. If you are interested in providing the technical expertise in challenging the current status-quo of AI infrastructure in real-world environments, join us in our path to a sustainable future of AI. WHAT YOU’LL DO - Own end-to-end technical enablement for US customers deploying AI models on FuriosaAI's RNGD NPU using the Furiosa SDK - Develop POCs, benchmarking studies, and live debugging sessions directly in customer environments - Act as the technical authority to the US BD/Sales team during pre-sales and enterprise evaluations; translate deep technical capability into business value for engineering and C-suite audiences - Develop deep, current expertise in FuriosaAI's hardware and software stack and demonstrate it at US technical forums, AI conferences, and customer workshops - Onboard and train customers on integration patterns, optimization workflows, and best practices post-purchase - Serve as a technical feedback loop from US customers back to Seoul HQ product and engineering teams QUALIFICATIONS - 2–5 years in a US customer-facing technical role: Solutions Architect, Sales Engineer, Forward Deployed Engineer, or equivalent at an AI infra, cloud, or semiconductor company - Actively current on the AI/LLM landscape — tracking model releases, inference frameworks, and serving stack evolution in real time - Hands-on experience with modern inference stacks: vLLM, SGLang, TensorRT-LLM, Triton Inference Server, or similar - Hands-on experience with agent and orchestration frameworks: LangChain, LlamaIndex, LangGraph, AutoGen, or MCP-based tooling - Proficiency in
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