Software Engineer, AI Application Engineer

Summary

The AI Application Engineer will develop and optimize AI applications and reference systems for FuriosaAI's hardware, bridging the gap between the software stack and market demand. The role involves integrating AI models, building end-to-end pipelines like RAG and agentic systems, and engaging with the open-source developer community.

About FuriosaAI

FuriosaAI builds high-performance, high-efficiency AI compute for the Inference Era. Founded in 2017 by veteran semiconductor and AI algorithm engineers, Furiosa operates globally with offices in Korea and Silicon Valley, along with a compiler-focused R&D lab in Lisbon.

Our vision is to make AI computing sustainable, enabling access to powerful AI for everyone on Earth. We solve the AI hardware energy and operational cost crisis at the architectural level, rather than through brute force, building the world's first truly AI-native compute platform to unlock the full potential of artificial intelligence for every enterprise.

About the Job

For the successful enabling of RNGD's global developer community, the AI Application Engineer will bridge the gap between FuriosaAI's software stack and market demand by developing a comprehensive AI application ecosystem, with high-impact AI applications and technical resources, centered around our FuriosaAI apps repository.

Furiosa-apps Repository:

Responsibilities

Model Enablement: Lead the integration of diverse AI models including VLA, Vision, and Multimodal architectures by utilizing our kernel programming model to ensure performance and developer readiness.
Reference Application Development: Build end-to-end applications such as RAG systems, agentic systems, RL inference engines, and Video processing pipelines by incorporating top-stack toolchains and industry-standard frameworks.
Ecosystem Development: Support live application demos and collaborate with the global developer community through GitHub and open-source channels to improve real-world usability.
Industry Leadership: Identify and prepare strategic contribution items for industry groups such as OCP to establish FuriosaAI’s technical leadership and market presence.

Minimum Qualifications

BS in Computer Science, Electrical Engineering, or a related field.
Experience in programming with Python, Rust, or other programming languages.
Experience in AI model implementation, optimization, and deployment using deep learning frameworks (PyTorch, HuggingFace), serving frameworks (vLLM, SGLang), and performance profiling tools.
Experience collaborating across engineering, product, and design teams to align software development with product requirements.

Preferred Qualifications

MS or PhD in Computer Science, Electrical Engineering, or a related field.
Experience in low-level systems programming or developing high-performance kernels for AI accelerators.
Experience in open-source or research projects on AI applications such as agentic systems, RAG, or multimodal pipelines.
Experience in strategic technical leadership, including authoring architectural guides or delivering technical presentations to industry-standard groups such as OCP.

Contact

recruit@furiosa.ai

Show