This role is hybrid, based out of Santa Clara, CA; Austin, TX; 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
Technically grounded, with experience in software engineering, systems engineering, or technical program management in a complex engineering environment.
Able to understand software architecture, system dependencies, and hardware/software interactions, and translate technical challenges into actionable plans.
Comfortable driving ambiguous, cross-functional initiatives involving multiple engineering teams, competing priorities, and evolving requirements.
Data-driven and proactive about identifying risks, investigating issues, and driving problems to resolution.
Hands-on and resourceful, with strong communication skills and an interest in using code, automation, dashboards, and AI-powered tools to improve engineering workflows.
What We Need
Drive end-to-end execution of complex platform engineering initiatives, from problem definition and technical planning through implementation, validation, and delivery.
Coordinate across runtime, device drivers, deployment, observability, debug tools, hardware, and architecture teams to manage dependencies and unblock engineering progress.
Lead reliability and scalability initiatives for AI systems, including fleet-scale deployment, cluster recovery, hardware/software integration, and resolution of recurring system issues.
Establish execution plans, milestones, success metrics, and reporting mechanisms that help engineering teams identify risks and make informed decisions.
Improve engineering execution through technical problem-solving, telemetry, dashboards, automation, and AI-assisted workflows while supporting platform readiness for new hardware and customer requirements.
What You Will Learn
How runtime systems, device drivers, and platform software work together to enable reliable, high-performance AI accelerators and end-to-end AI systems at scale, from individual devices to distributed compute clusters.
How software, firmware, hardware, and observability systems come together to deliver production-ready AI platforms.
How to lead technically complex initiatives across multidisciplinary engineering teams.
How to use data, automation, and AI-powered tools to improve engineering execution and operational efficiency.
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.
