Solutions Architect - US

About this role

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 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

PREFERRED QUALIFICATIONS

- 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

CONTACT

- [email protected]