Solutions ArchitectFuriosaAI 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 DoOwn end-to-end technical enablement for US customers deploying AI models on FuriosaAI's RNGD NPU using the Furiosa SDKDevelop POCs, benchmarking studies, and live debugging sessions directly in customer environmentsAct 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 audiencesDevelop deep, current expertise in FuriosaAI's hardware and software stack and demonstrate it at US technical forums, AI conferences, and customer workshopsOnboard and train customers on integration patterns, optimization workflows, and best practices post-purchaseServe as a technical feedback loop from US customers back to Seoul HQ product and engineering teamsQualifications2–5 years in a US customer-facing technical role: Solutions Architect, Sales Engineer, Forward Deployed Engineer, or equivalent at an AI infra, cloud, or semiconductor companyActively current on the AI/LLM landscape — tracking model releases, inference frameworks, and serving stack evolution in real timeHands-on experience with modern inference stacks: vLLM, SGLang, TensorRT-LLM, Triton Inference Server, or similarHands-on experience with agent and orchestration frameworks: LangChain, LlamaIndex, LangGraph, AutoGen, or MCP-based toolingProficiency 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 executivesAuthorized to work in the US; able to travel to customer sites and to Seoul HQ periodicallyPreferred QualificationsPrior experience at a US AI chip company, cloud silicon team, or AI infrastructure startupFamiliarity with NPU/GPU accelerator ecosystems, PCIe integration, and data center hardware deploymentExperience with inference optimization: quantization, kernel tuning, batching strategies, memory bandwidth optimizationProficiency in C, C++, or RustExperience working with distributed or cross-timezone engineering