<p>About the Job</p> <p>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.</p> <p>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.</p> <p>What You'll Do</p> <ul> <li> <p>Own end-to-end technical enablement for US customers deploying AI models on FuriosaAI's RNGD NPU using the Furiosa SDK</p> </li><li> <p>Develop POCs, benchmarking studies, and live debugging sessions directly in customer environments</p> </li><li> <p>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</p> </li><li> <p>Develop deep, current expertise in FuriosaAI's hardware and software stack and demonstrate it at US technical forums, AI conferences, and customer workshops</p> </li><li> <p>Onboard and train customers on integration patterns, optimization workflows, and best practices post-purchase</p> </li><li> <p>Serve as a technical feedback loop from US customers back to Seoul HQ product and engineering teams</p> </li></ul> <p>Qualifications</p> <ul> <li> <p>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</p> </li><li> <p>Actively current on the AI/LLM landscape - tracking model releases, inference frameworks, and serving stack evolution in real time</p> </li><li> <p>Hands-on experience with modern inference stacks: vLLM, SGLang, TensorRT-LLM, Triton Inference Server, or similar</p> </li><li> <p>Hands-on experience with agent and orchestration frameworks: LangChain, LlamaIndex, LangGraph, AutoGen, or MCP-based tooling</p> </li><li> <p>Proficiency in Python; comfortable with DNN frameworks (PyTorch, TensorFlow)</p> </li><li> <p>Strong written and verbal communication - able to engage credibly with ML engineers at frontier labs and VP/C-suite executives</p> </li><li> <p>Authorized to work in the US; able to travel to customer sites and to Seoul HQ periodically</p> </li></ul> <p>Preferred Qualifications</p> <ul> <li> <p>Prior experience at a US AI chip company, cloud silicon team, or AI infrastructure startup</p> </li><li> <p>Familiarity with NPU/GPU accelerator ecosystems, PCIe integration, and data center hardware deployment</p> </li><li> <p>Experience with inference optimization: quantization, kernel tuning, batching strategies, memory bandwidth optimization</p> </li><li> <p>Proficiency in C, C++, or Rust</p> </li><li> <p>Experience working with distributed or cross-timezone engineering teams</p> </li></ul> <p>Contact</p> <ul> <li>recruit@furiosa.ai </li></ul>