Senior / Staff Technical Program Manager - Datacenter Capacity Delivery (e2e)

Cerebras Cerebras · Semiconductors · Headquarters +1 · Datacenters

This role is for a Senior/Staff Technical Program Manager responsible for the end-to-end delivery of data center capacity for AI workloads. The role involves managing the entire lifecycle from planning to operational readiness, orchestrating cross-functional teams, and ensuring alignment with AI infrastructure and hardware deployment schedules. While the company builds AI hardware and the role supports AI workloads, the core function is data center capacity delivery, not direct AI/ML model development or research.

What you'd actually do

  1. Own delivery of AI-optimized data center capacity (colo, build-to-suit, retrofits, and owned facilities) from pre-contract planning through operational readiness.
  2. Deliver MW-scale infrastructure aligned to aggressive GPU/AI system deployment targets.
  3. Drive clarity from ambiguity—translate high-level demand signals into executable delivery programs.
  4. Decompose complex build programs into workstreams with clear owners, milestones, and deliverables.
  5. Build integrated plans spanning real estate, power/energy, design, procurement, construction, and deployment.

Skills

Required

  • 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
  • Ability to operate in high-growth, ambiguous environments with limited structure
  • Strong executive presence and ability to influence without authority
  • Clear, structured communicator who can turn chaos into executable plans
  • Bias for action with a track record of delivering results under pressure

Nice to have

  • Experience at hyperscalers (Google, Meta, Microsoft, AWS) or neo-cloud / AI infra companies (CoreWeave, Lambda, etc.)
  • Familiarity with high-density AI workloads (liquid cooling, >30kW racks, GPU clusters)
  • Experience with: (Note: Specific experience listed here is incomplete in the source text)
  • Extreme ownership mindset

What the JD emphasized

  • ambiguity is high
  • timelines are compressed
  • stakes are critical to company growth
  • critical risks
  • aggressive GPU/AI system deployment targets
  • aggressive schedule compression
  • high-density AI workloads
  • high-growth, ambiguous environments with limited structure
  • delivering results under pressure