Forward Deployed Engineer

Tenstorrent|27 Oct 2026

fulltimeonsite

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Before you apply

Listed location: Austin, Texas, United States; Santa Clara, California, United States; Toronto, Ontario, Canada

Work arrangement: onsite. A remote label does not confirm worldwide eligibility or visa sponsorship.

Read the employer’s description for qualifications, compensation and work eligibility. Confirm the position is still open on the application page.

Job description supplied by Tenstorrent; category and skill labels may be inferred. How our listings work · Report a problem

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.

We’re looking for a Forward Deployed Engineer to own the technical outcome of the AI Hardware systems we build with our customers. You will work alongside customer engineering and operations teams to make complete systems work in production or near-production environments. This engineering role spans hardware and software integration, deployment, validation, automation, debugging, and ongoing operations. You will contribute to customer deployments, establish reliable operating procedures, and drive customer systems through resolution until they work as intended.

This role is hybrid, based out of Santa Clara, California, Austin, Texas or Toronto, Canada.

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

You take ownership of customer outcomes in deployed environments through integration, validation, production readiness, and operations.
You understand how accelerator compute, memory, and networking topology constrain AI workloads, and don’t treat hardware as a black box.
You work directly with customer engineering and operations teams to understand their environment, constraints, and desired outcomes.
You’re comfortable debugging across the inference stack, from failing requests, kernel dispatch, drivers, networking, or hardware behavior.
You automate repetitive work and communicate technical trade-offs clearly with both customer leadership and core engineering teams.

What We Need

Minimum Requirement

Hands-on experience with Server hardware in a Datacenter environment.
Experience troubleshooting complex issues with hardware and software.
Experience with Linux systems administration, including knowledge of debugging OS issues.
Previous experience in one of the following roles: Site Reliability Engineer, Systems Engineer, Platform Engineer, or Infrastructure Engineer.

Preferred requirement

Experience working with and troubleshooting GPUs, PCIe devices, or large clusters.
Strong software engineering skills in Python; C++ experience is a plus.
Experience turning ambiguous requirements into production-ready implementations, acceptance criteria, validation plans, and operating procedures.
Kubernetes and Linux systems administration experience at multi-node, HPC, or AI cluster scale, including Kubernetes orchestration.
Experience with observability, infrastructure automation, CI/CD, release engineering, and LLM support.
A desire to travel in the region to support deployments is a strong plus.

What You Will Learn

How co-design across AI hardware and software translates silicon capabilities into measurable latency and throughput gains.
How to operate disaggregated inference systems on Kubernetes while balancing performance, reliability, maintainability, and cost.
How to take enterprise AI deployments from requirements through integration, software delivery, validation, production readiness, and ongoing ownership.
How customer deployment and operational insights shape product improvements and platform direction.

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 information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.

Frequently asked questions

Is the Forward Deployed Engineer position at Tenstorrent remote?

The Forward Deployed Engineer role at Tenstorrent does not have a confirmed remote arrangement in our data. Check the employer description for its work location.