Global Engineering Process Leader — AI-Driven Excellence

Vertiv

Novi (MI)

On-site

USD 120,000 - 180,000

Full time

14 days+

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Job summary

Vertiv seeks a Global Engineering Process Lead, Sr. Manager to optimize product development across its worldwide engineering teams. You will drive DFSS, FMEA, and traceability while deploying AI-enabled tools to cut design cycle times and boost quality.

Based onsite in Westerville, OH or Novi, MI, you will lead cross-functional initiatives, measure design release efficiency and process adherence, and partner with tool owners to align workflows with PLM and simulation platforms.

Qualifications

Bachelor’s degree in mechanical, electrical, industrial engineering or related field; master’s preferred.
10–15 years in engineering with focus on process improvement and product development.
Experience implementing DFSS, DFMEA/PFMEA, and end-to-end traceability.
Experience adopting AI-enabled engineering tools and digital platforms.
Strong analytical, collaboration, and project governance skills.

Responsibilities

Improve engineering efficiency by identifying best practices, streamlining workflows, eliminating non-value-added activities, and optimizing global engineering processes to reduce design cycle times and improve productivity.
Standardize engineering processes across all product lines by driving process convergence, governance, requirements management and traceability, Design for Six Sigma (DFSS) methodologies, FMEA best practices, and continuous improvement initiatives that improve quality, consistency, scalability, and design robustness.
Promote and deploy AI-enabled engineering solutions and digital technologies to automate engineering workflows, improve knowledge management, support requirements traceability, accelerate design activities, enhance engineering decision-making, and improve overall engineering effectiveness.
Collaborate with engineering tool owners, quality leaders, systems engineering teams, and cross-functional stakeholders to ensure seamless integration between engineering processes, management systems, PLM systems, simulation tools, AI platforms, and product development workflows while maintaining end-to-end requirements traceability.
Define, track, and improve key engineering metrics including design cycle time, engineering productivity, rework rates, first-pass quality, requirements traceability compliance, FMEA effectiveness, design release efficiency, and process adherence.