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).