AI Systems Engineer – TT-Fabric Networking & Scaling

Tenstorrent; Santa Clara, Austin (CA, TX); Hybrid; USD 100,000 - 500,000; Full time

Job summary

Tenstorrent is building high‑performance AI compute clusters and TT‑Fabric, the low‑level networking layer that connects thousands of RISC‑V and AI processors. We seek engineers who can architect and implement scalable networking for distributed inference and training in a hybrid role based in Santa Clara, Austin, or Toronto.

The role welcomes a range of experience levels; offers align with the level and location, with a highly competitive compensation package and equity potential.

Qualifications

• Strong systems engineer with deep C or C++ experience in low-level or bare-metal environments.
• Experience with distributed systems and high-performance networking.
• Familiarity with RISC-V is a plus.

Responsibilities

• Architect, implement, and maintain TT‑Fabric, our low‑level networking library powering distributed inference and training.
• Design scalable communication systems capable of coordinating thousands of AI processors efficiently and reliably.
• Optimize protocols, synchronization strategies, and data movement to extract maximum hardware performance.
• Integrate TT‑Fabric APIs into the broader programming model in collaboration with AI and hardware teams.
• Help define the long‑term architecture of Tenstorrent’s distributed systems stack.

Skills

C/C++ programming

Low-level development

Distributed systems

Networking

Education

Bachelor's degree in Computer Science or related field

Tools

TT-Fabric

Job description

Tenstorrent is building high‑performance AI compute clusters and TT‑Fabric, the low‑level networking layer that connects thousands of RISC‑V and AI processors. We seek engineers who can architect and implement scalable networking for distributed inference and training in a hybrid role based in Santa Clara, Austin, or Toronto.

The role welcomes a range of experience levels; offers align with the level and location, with a highly competitive compensation package and equity potential.