Solutions Architect US

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 RNGDs powerful system to real-world deployments of customers models empowering customers with FuriosaAIs 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.

• Own end-to-end technical enablement for US customers deploying AI models on FuriosaAIs 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 FuriosaAIs 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

• 25 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 Python; comfortable with DNN frameworks (PyTorch TensorFlow)

• Strong written and verbal communication able to engage credibly with ML engineers at frontier labs and VP/C-suite executives

• Authorized to work in the US; able to travel to customer sites and to Seoul HQ periodically

• 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

Required Experience:

Staff IC