Deployment Network Manager
Cerebras
Deployment Network Manager
Cerebras
AI accelerator hardware replacing GPUs
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 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.
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
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
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.
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
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
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
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
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:
Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
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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Cerebras Systems creates AI acceleration hardware and software. Its CS-2 system is designed to replace traditional GPU clusters for AI workloads, speeding up training and inference while simplifying the setup by eliminating the need for parallel programming, distributed training, and cluster management. The product works as a single, large processor-based accelerator with accompanying software and cloud services to run AI models efficiently, reducing latency and time to results. Compared with competitors, Cerebras differentiates itself with the largest processor in the industry and an integrated hardware-software stack that aims to streamline AI workflows rather than relying on multi-GPU clusters. The company's goal is to help research labs, healthcare, finance, and other industries achieve faster, more cost-effective AI development and deployment by offering a turnkey high-performance AI compute solution.
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