AI SW DC Deployment Staff Technical Program Manager Toronto, Ontario, Canada

Tenstorrent Inc.

Toronto

Hybrid

CAD 140,000 - 190,000

Full time

43 hours ago
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Job summary

Tenstorrent Inc. is seeking a Staff/Senior Staff Technical Program Manager for Data Center Deployment and SRE.

You will drive programs spanning hardware, software, and data-center operations, aligning dependencies and engineering workflows to scale deployments with automation and data-driven insights. You will partner closely with hardware, firmware, compiler, and software teams, translating metrics and risks into clear executive reporting and actionable plans.

Qualifications

  • Lead cross-functional programs spanning hardware, software, and data center operations.
  • Strong understanding of computer architecture, OS, runtimes, and HW/SW interfaces.
  • Ability to translate signals and metrics into executive reporting.

Responsibilities

  • Own complex programs bridging hardware, firmware, software, and deployment teams.
  • Connect dependencies and operational data to improve deployment and scaling.
  • Lead with automation, dashboards, and data to enhance visibility and decision making.
  • Communicate risks, trade-offs, and decisions to senior leadership.

Skills

Technical leadership
Cross-functional collaboration
Systems thinking
Data-driven decision making
Automation and tooling

Education

Bachelor’s degree in Computer/Electrical Engineering or related field

Tools

APIs
Telemetry
Data pipelines
CI/CD
SQL
Python
Scripting

Job description

Staff Technical Program Manager, Data Center Deployment

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.

As a Staff or Senior Staff Technical Program Manager on the Data Center Deployment and SRE team, you will drive complex programs spanning hardware, software, infrastructure, and data center operations. You will connect technical dependencies, operational data, and engineering workflows to improve how systems are deployed and scaled. This role combines deep technical understanding with hands-on program leadership, using automation and data to improve execution, visibility, and decision-making across teams.

This role ishybrid, based out of 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

  • A self-directed technical leader who can take ambiguous, cross-functional problems and turn them into structured, executable programs.
  • A systems thinker with a strong understanding of computer architecture, operating systems, runtime systems, and the dependencies between hardware and software.
  • Hands-on with data, tooling, and automation, with the ability to connect systems and improve the quality and accessibility of program information.
  • An effective technical partner who can work deeply with engineering teams while communicating risks, tradeoffs, and decisions clearly to senior leadership.

What We Need

  • Bachelor’s degree or higher in Computer Engineering, Electrical Engineering, or a related field.
  • 5+ years leading complex technical programs, tooling initiatives, or data-driven engineering operations as a TPM, technical lead, or cross-functional owner.
  • Strong understanding of computer architecture and systems, including processors, memory hierarchies, interconnects, operating systems, runtimes, and hardware-software interfaces.
  • Technical depth to identify dependencies, evaluate tradeoffs, and drive execution across hardware, firmware, compilers, software, infrastructure, and deployment teams.
  • Experience building scalable workflows and automation using APIs, telemetry, data pipelines, dashboards, CI/CD, SQL, Python, scripting, and engineering management platforms, with the ability to translate technical signals, metrics, risks, and dependencies into clear executive-level reporting.

What You Will Learn

  • How Tenstorrent deploys and operates complex AI hardware and software systems across large-scale data center environments.
  • How architecture, firmware, compilers, software, infrastructure, and deployment interact throughout the lifecycle of an AI system.
  • How to apply automation and AI-enabled tooling to improve technical program execution, operational visibility, and decision-making.
  • How to shape the tooling, processes, and operating model used to scale deployment and SRE programs across Tenstorrent.

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.

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