Junior Solution Architect

You will analyze customer requirements and technical constraints, then propose suitable AI inference environments and implementation approaches. You will develop and improve inference programs, examples, and demos using the Furiosa SDK. You will validate technical feasibility through proof-of-concepts, document results and technical issues, and evaluate latency, throughput, and model accuracy. You will explain product capabilities and validation results to customers, partners, and developers, prepare guides and training materials, and share customer feedback and technical issues with engineering stakeholders.

Responsibilities

• Analyze customer requirements and technical constraints and propose inference solutions
• Develop and improve inference programs, examples, and demos using the Furiosa SDK
• Validate technical feasibility through proof-of-concepts and document results and technical issues
• Evaluate inference performance, latency, throughput, and model accuracy
• Analyze changes from SDK updates and differences from GPU and other execution environments
• Explain product capabilities and validation results to customers, partners, and developers
• Create usage guides and training materials
• Share customer technical issues and feedback with engineering stakeholders

Requirements

• Bachelor's degree in computer science or a related field, or equivalent experience
• Write and modify Python programs and analyze execution results and errors
• Analyze problem causes using data and experiments and validate solutions
• Clearly explain technical content and decision rationale and collaborate by asking for and sharing needed information
• Demonstrate capabilities through professional, academic, research, internship, personal-project, or open-source experience
• Experience developing and operating in Linux environments
• Experience with C, C++, or Rust
• Experience automating development, testing, or benchmarking with scripts
• Experience with LLM serving and inference optimization tools such as vLLM, SGLang, or TensorRT-LLM
• Experience with Docker or Kubernetes
• Experience designing benchmarks or evaluating model accuracy
• Experience in presales or B2B technical support