RISC-V AI / HPC & Agentic Software Engineering Lead
TenstorrentNorth America$100k – $500kPosted 7 April 2026
Job Description
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.
Tenstorrent is building next-generation RISC-V CPUs optimized for AI, high-performance computing, and emerging autonomous AI systems. As the RISC-V AI / HPC Agentic Software Engineering Lead, you will operate at the hardware–software boundary, enabling AI, HPC, and agentic AI software stacks on Tenstorrent’s RISC-V processors. This role is responsible for integrating and optimizing Tenstorrent’s LLK (Low-Level Kernel) infrastructure for CPU execution, while leading the bring-up of a RISC-V-native agentic AI software stack — including runtime orchestration, distributed execution frameworks, memory systems, and developer tools required for goal-driven AI systems. You will work closely with CPU architects, microarchitecture teams, compiler engineers, and AI kernel developers to ensure tight alignment between software capabilities and RISC-V architectural features.
This role is
remote, based out of North America.
We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.
Who You Are
A systems-oriented software engineer with deep experience in HPC and AI software stacks.
Experienced with distributed AI systems, orchestration frameworks, or agentic AI architectures.
Comfortable working close to hardware and instruction-level programming.
Skilled at translating performance targets into architectural and software requirements.
Experienced in runtime systems, profiling, and low-level optimization.
Motivated by hardware–software co-design and scaling next-generation AI infrastructure.
What We Need
Strong background in HPC and AI software development.
Solid understanding of RISC-V architecture (ISA, extensions, micro-architectural implications).
Proficiency in C/C++ and systems programming.
Experience optimizing performance-critical code paths.
Experience with agentic AI frameworks, distributed execution systems, or orchestration platforms.
Familiarity with compiler toolchains (LLVM, GCC).
Experience with vectorization, custom ISA extensions, or accelerator integration.
What You Will Learn
How AI and agentic workloads map to RISC-V microarchitecture.
Custom ISA extension design for AI acceleration.
End-to-end HPC/AI/agentic stack integration.
Runtime orchestration for distributed AI systems.
Hardware–software co-design for scalable AI-native CPU platforms.
Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.
Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.
This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to ... (truncated, view full listing at source)
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