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Cerebras

Deployment Network Manager – Global Data Center Build and Deploy

Cerebras is hiring a Deployment Network Manager – Global Data Center Build and Deploy for a remote role open to applicants in United States. Level rates it ; you can apply on Cerebras.

Level's read on this job

  • On Level's scale, this role is Works on AI ●●●○: the daily work is on AI products, without building the model.
  • This is listed as a remote role.
  • The posting mentions OpenAI and AI research among its tools and skills.
  • Level classes it as a senior role.
  • Cerebras has 120 other open roles on Level.

AI in this role

OpenAI
ai-research

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.

This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.

Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.

The Role

The Deployment Manager – Global Data Center Build and Deploy is responsible for the end-to-end execution of AI cluster deployments within large-scale data centers, specifically taking from facility ready for power and cooling to customer hand-off. This role leads rack integration, high-density inter-rack cabling, and close coordination with facilities, networking, and operations teams to deliver Cerebras Wafer Scale Engine based clusters safely, on schedule, and to strict quality standards.

The ideal candidate has deep experience deploying AI infrastructure, understands the operational demands of high-power, high-thermal-density environments, and excels at troubleshooting complex cabling and integration issues. This role requires providing directions to technicians on the Data Center floor, and resolve any issue blocking build and deploy in data centers. The role requires traveling and physically present at Data Center weeks at a time.

Responsibilities

AI Cluster Deployment & Rack Integration

  • Lead deployment of AI clusters including Cerebras Wafer Scale Engine, high-speed switches, storage, and rack-level infrastructure

  • Coordinate rack integration of high-density compute, specialized racks, and associated power components (PDUs, busway drops)

  • Ensure deployment aligns with AI cluster architecture, topology, and scaling requirements

High-Density Inter-Rack & Intra-Rack Cabling

  • Manage installation of high-speed interconnect cabling (fiber and copper) supporting AI fabrics (east–west traffic) in Data Centers

  • Coordinate inter-rack and intra-rack cabling for AI clusters, including spine-leaf and pod-level designs

  • Ensure proper routing, airflow clearance, labeling, and testing of all AI-related cabling

Facilities & Infrastructure Coordination

  • Work closely with facilities teams on power capacity, cooling readiness, containment, and grounding for dense racks

  • Coordinate deployment sequencing with facility commissioning milestones

  • Validate white-space readiness before rack and cluster deployment

  • Provide directions to technicians on the data center floor.

Troubleshooting & Issue Resolution

  • Troubleshoot cabling, connectivity, and integration issues impacting AI cluster bring-up

  • Lead root-cause analysis for deployment blockers related to cabling, hardware placement, or facilities dependencies

  • Support validation, burn-in, and handoff of AI clusters to operations teams

Cross-Functional Execution

  • Partner with network, server, AI platform, and operations teams to align on deployment plans and readiness

  • Manage multiple parallel AI cluster deployments across sites or availability zones

  • Communicate risks, dependencies, and milestones clearly to stakeholders

Quality, Standards & Documentation

  • Ensure deployments follow company design standards, structured cabling best practices, and AI deployment playbooks

  • Validate as-built documentation, labeling accuracy, and deployment checklists

  • Maintain accurate records for cluster configuration, cabling, and deployment status

Safety & Risk Management

  • Enforce EHS, data center safety, and access control procedures during deployment

  • Ensure safe handling of heavy, high-power GPU equipment

  • Proactively identify and mitigate deployment and operational risks

Qualifications

  • Bachelor’s degree in Engineering, IT, or equivalent practical experience

  • 10+ years of experience in data center deployments, infrastructure delivery, or integration roles

  • Ability to provide directions to technicians on data center floor.

  • Hands-on experience deploying hyperscale AI, ML, or HPC infrastructure

  • Strong experience with structured cabling in high-density environments, and troubleshooting

  • Proven ability to manage complex, cross-functional deployment programs

  • Familiarity with high-speed fabrics (e.g., InfiniBand, high-bandwidth Ethernet)

  • Experience with DCIM or deployment tracking systems

  • Strong attention to detail and operational rigor

  • Ability to perform under tight timelines and production constraints

Why Join Cerebras

People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:

  1. Build a breakthrough AI platform beyond the constraints of the GPU.

  2. Publish and open source their cutting-edge AI research.

  3. Work on one of the fastest AI supercomputers in the world.

  4. Enjoy job stability with startup vitality.

  5. Our simple, non-corporate work culture that respects individual beliefs.

Find out more about what it's like to work at Cerebras here!

Apply today and become part of the forefront of groundbreaking advancements in AI!

Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

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How we rate this

Deployment Network Manager – Global Data Center Build and Deploy at Cerebras rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI ResearchOpenAI

Questions you could be asked

  1. Tell me about a research question you investigated. What did you find?
  2. Walk me through how you've used OpenAI in your day-to-day work.
  3. Describe a typical day in a role like this one: which parts run through AI directly?
  4. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: AI Research and OpenAI. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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