Staff Technical Program Manager, Data Center Deployment at Tenstorrent in Toronto, ON

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. As a Staff or Senior Staff Technical Program Manager on the Data Center Deployment team, you will drive complex programs across AI hardware, software, infrastructure, and data center operations. You will work closely with engineering and operations teams to understand system-level dependencies, troubleshoot deployment and operational issues, and improve the reliability and scalability of our infrastructure. This role requires more than program coordination: you will use operational data, technical debugging, scripting, and automation to improve workflows, surface risks, and drive data-informed decisions across teams. This role is hybrid, 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 technically hands-on program leader with direct experience in data center infrastructure, systems deployment, SRE, or infrastructure operations. A systems thinker who can investigate technical issues, lead detailed debugging and triage, and understand dependencies across hardware, firmware, networking, operating systems, and software. A data-driven problem solver who uses telemetry, monitoring, observability, metrics, and dashboards to identify issues, assess impact, and guide decisions. A builder who has personally developed scripts, workflows, or automations to reduce manual work, improve operational efficiency, and increase visibility. An AI-forward technical partner who actively uses AI tools to accelerate analysis, automation, and program execution while communicating technical risks and tradeoffs clearly. What We Need Bachelor’s degree or higher in Computer Engineering, Electrical Engineering, Computer Science, or a related technical field, with 5+ years leading complex technical programs, infrastructure initiatives, or data-driven engineering operations. Direct data center infrastructure or systems operations experience, including an understanding of deployment, hardware and software dependencies, capacity or resource allocation, reliability, and operational constraints at scale. Strong technical troubleshooting skills, including driving detailed debugging, incident triage, and root cause analysis across interconnected hardware, firmware, networking, operating systems, and software systems. Hands-on experience with observability and operational tooling, including telemetry, monitoring, logs, metrics, dashboards, and data pipelines, to investigate issues and track system health, performance, and reliability. Demonstrated ability to personally build and maintain automation, scripts, or workflows using Python, SQL, APIs, shell scripting, or similar tools; regularly use AI-assisted tools to improve workflows, automate repetitive tasks, analyze data, and accelerate technical problem-solving; and translate findings into actionable plans and clear stakeholder reporting. What You Will Learn How Tenstorrent deploys, debugs, and operates complex AI hardware and software systems across large-scale data center environments. How hardware, firmware, networking, operating systems, software, and infrastructure interact throughout the deployment and operational lifecycle of AI systems. How to use operational