Director leading enterprise data governance, catalog, quality, and AI readiness for CBC/Radio - Canada’s public service media organization. Hybrid role guiding governance programs, councils, stakeholders, and data teams.
About the role
- AI Data Center Infrastructure Engineer designing racks, power, cabling, and network layouts for Cerebras’ large-scale AI chip systems. Automating deployment workflows and integrating compute infrastructure.
Responsibilities
- Translate cluster architectures and technical requirements into complete, deployment-ready infrastructure designs
- Produce and maintain rack elevations, equipment layouts, bills of materials, power allocations, port maps, and cable maps
- Adapt reference designs to site-specific space, power, cooling, connectivity, logistics, and hardware constraints
- Validate compute, storage, networking, power, and cabling designs as an integrated system
- Evaluate trade-offs balancing performance, reliability, scalability, cost, serviceability, and deployment schedule
- Partner with systems, network, hardware, manufacturing, supply-chain, and data center operations teams
- Participate in design and deployment-readiness reviews and identify risks, inconsistencies, and missing requirements
- Support deployment teams by resolving physical integration issues and documenting approved design changes
- Contribute to root-cause analysis of deployment or integration problems
- Develop scripts and tools to automate design generation, BOM creation, cable mapping, consistency checks, and repeatable workflows
- Improve templates, standards, documentation, and design processes for repeatable, scalable deployments
Requirements
- A bachelor’s or master’s degree in computer engineering, electrical engineering, computer science, or a related discipline—or equivalent practical experience
- One or more years of relevant experience in infrastructure engineering, data center design, systems integration, hardware deployment, or a related field
- Experience creating or working with rack elevations, equipment layouts, bills of materials, port maps, or cable maps
- Practical understanding of server, storage, and networking hardware and their physical integration
- Familiarity with data center power, cooling, space, cabling, and serviceability constraints
- Experience using Python, Bash, PowerShell, or another language to automate technical workflows
- Strong analytical skills and close attention to detail
- Ability to turn incomplete or changing requirements into clear, actionable designs
- Clear written and verbal communication skills and ability to collaborate across engineering disciplines
- Experience with high-speed Ethernet or InfiniBand networks, optical transceivers, fiber, DACs, or structured cabling is valuable but not required
- Experience using infrastructure documentation, diagramming, DCIM, CAD, or source-controlled design tools is valuable but not required
- Experience developing automated validation, configuration-generation, or infrastructure-modeling tools is valuable but not required
- Experience supporting data center deployment, commissioning, hardware integration, or deployment-related incident analysis is valuable but not required
- Experience working with contract manufacturers, colocation providers, installation partners, or supply-chain teams is valuable but not required
Benefits
- Build a breakthrough AI platform beyond the constraints of the GPU
- Publish and open source cutting-edge AI research
- Work on one of the fastest AI supercomputers in the world
- Job stability with startup vitality
- Simple, non-corporate work culture that respects individual beliefs
- Equal and diverse work environment
- Continuous learning, growth and support
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