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Principal Technical Program Manager (Hardware)

Hayden AI

Skills

Required

  • Hardware
  • TPM / Engineering
  • M.S
  • Program Management
  • NPI lifecycle
  • EVT
  • DVT
  • PVT
  • MP
  • phase gate governance
  • CM/supplier management

Preferred

  • autonomous systems / robotics / AI/ML hardware programs
  • DFX methodologies
  • DFI
  • DFS
  • phase gate reviews
  • hardware lifecycle
  • embedded systems / hardware/software integration / computer vision systems

Join our team as a Principal Technical Program Manager (Hardware) where you will lead the development and execution of a portfolio of hardware programs. You will collaborate with leaders across the organization to drive strategy into roadmaps and plans that deliver critical work on time and at high quality. You will set the standard for program excellence across the entire product lifecycle and drive systemic improvements across the company.

USD 213,743 - 277,866

About Hayden AI

Experience with hardware reliability, regulatory compliance (FCC, CE), and supply chain risk

Responsibilities

  • Lead the development and execution of a portfolio of hardware programs, ensuring timely delivery and high quality.
  • Drive end-to-end delivery of enterprise engineering programs, bridging executive business goals and technical execution.
  • Define, implement, and rigorously enforce phase gate reviews and program milestones across the hardware lifecycle.
  • Strong technical foundation in embedded systems, hardware/software integration, or computer vision systems

Requirements

B.S., M.S., or Ph.D. in an engineering discipline

  • Led 5+ multi-disciplinary hardware products from 0-to-1 through production
  • 12+ years in Hardware TPM or Engineering Program Management
  • Deep knowledge of NPI lifecycle (EVT, DVT, PVT, MP), phase gate governance, and CM/supplier management
  • Experience delivering technology to government or municipal clients

Preferred

  • Experience with on-vehicle, edge-deployed, or ruggedized hardware
  • Background in autonomous systems, robotics, or AI/ML hardware programs
  • Familiarity with DFX methodologies (DFA, DFI, DFS)