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Cerebras

Staff TPM - Datacenter Delivery (E2E)

Cerebras is hiring a Staff TPM - Datacenter Delivery (E2E) for a remote role open to applicants in United States. Level rates it ; you can apply on Cerebras.

Level's read on this job

  • Little AI ●○○○ is how Level rates this role: aI is not part of the work.
  • The posting lists this role as remote.
  • Tools and skills the posting cites include OpenAI and AI research.
  • Level lists 120 other open roles at Cerebras.
  • The role was posted within the past week.

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.

About The Role

The DC Delivery E2E TPM is the single-threaded owner for delivering data center capacity from forecast → site strategy → design → construction → infrastructure readiness → go-live.

You will operate as the SSOT (Single Source of Truth) for delivery milestones, risks, and capacity outcomes while orchestrating cross-functional execution across internal teams and external partners. This is a frontier-scale role where ambiguity is high, timelines are compressed, and stakes are critical to company growth.

Responsibilities

End-to-End Capacity Delivery

  • Own delivery of AI-optimized data center capacity (colo, build-to-suit, retrofits, and owned facilities) from pre-contract planning through operational readiness.

  • Deliver MW-scale infrastructure aligned to aggressive GPU/AI system deployment targets.

  • Drive clarity from ambiguity—translate high-level demand signals into executable delivery programs.

Program Structuring & Execution

  • Decompose complex build programs into workstreams with clear owners, milestones, and deliverables.

  • Build integrated plans spanning real estate, power/energy, design, procurement, construction, and deployment.

  • Establish critical path visibility and aggressively manage schedule compression.

Cross-Functional Leadership

  • Orchestrate execution across:

    • Real estate & site selection

    • Power & energy strategy (utilities, PPAs, interconnects)

    • Data center design (MEP, liquid cooling, high-density racks)

    • Supply chain & long-lead equipment procurement

    • Construction & commissioning

    • Infrastructure deployment (rack/cluster install)

    • Networking & backbone connectivity

    • Security, compliance, and operations readiness

  • Act as the primary interface with colocation providers, EPCs, utilities, and key vendors.

Risk, Cost & Governance

  • Identify and drive resolution of critical risks, constraints, and blockers across power, equipment, permitting, and supply chain.

  • Own and maintain program budgets, CapEx forecasts, and capital allocation narratives.

  • Provide structured updates and escalation paths to executive leadership.

Demand & Capacity Planning Integration

  • Partner with capacity planning, AI infrastructure, and finance teams to translate model demand into site-level capacity strategies.

  • Align build plans with power availability, network topology, and hardware rollout schedules.

  • Continuously optimize for time-to-capacity and cost-per-MW / cost-per-GPU deployed.

Operational Excellence

  • Drive E2E improvements in delivery through:

    • Standardization of build and commissioning processes

    • Implementation of program tooling and dashboards

    • Post-mortems and lessons learned loops

  • Establish scalable mechanisms to support rapid global expansion.

Communication & Leadership

  • Serve as SSOT for program health, milestones, and risks.

  • Deliver concise, high-signal updates to senior executives.

  • Operate effectively across distributed teams with up to 50% travel.

Skills & Qualifications

  • 12-15+ years in mission-critical facilities or data center operations

  • Experience managing multi-site, vendor-heavy environments

  • Strong expertise in electrical and mechanical systems

  • Proven track record in improving uptime and performance

Preferred Qualifications

  • Experience at hyperscalers (Google, Meta, Microsoft) or neo-cloud / AI infra companies (CoreWeave, Lambda, etc.).

  • Familiarity with high-density AI workloads (liquid cooling, >30kW racks, GPU clusters).

  • Experience with:

    • Utility engagement and power delivery constraints

    • Long-lead supply chain planning (transformers, switchgear, chillers)

    • Commissioning and data center handover processes

  • Ability to operate in high-growth, ambiguous environments with limited structure.

  • Strong executive presence and ability to influence without authority.

What sets you apart

  • Extreme ownership mindset — you treat capacity delivery as a personal SLA.

  • Ability to move fast without breaking systems, balancing urgency with rigor.

  • Comfort operating at the intersection of hardware, real estate, and software scaling demands.

  • Clear, structured communicator who can turn chaos into executable plans.

  • Bias for action with a track record of delivering results under pressure.

Location: US (preferred SF Bay Area / remote with travel)

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

Staff TPM - Datacenter Delivery (E2E) at Cerebras rates 14 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  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.

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Skills and AI tools this role asks for

AI ResearchOpenAI

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