Head of AI

PennEngineering®Waterford, MI
Onsite

About The Position

The Head of AI for the Business Unit is the senior leader responsible for the BU’s AI strategy and execution, with a mandate to convert AI capability into measurable business performance. Reporting to the BU President, this role owns the BU’s AI roadmap end-to-end: from mapping the BU’s processes, to scoring automation opportunities by ROI and feasibility, to building and deploying AI-powered solutions, to driving adoption and measuring the resulting business impact across productivity, quality, speed, margin, and decision-making. This is a hands-on leadership role. The Head of AI manages a small team of Forward Deployed Engineers (FDEs) embedded in the BU’s departments, partners with the central AI Enablement function at corporate for platform support, and engages with the company-wide AI Steering Committee on cross-BU patterns. We are looking for a leader senior enough to be credible with the BU President and to operate a function independently — but hands-on enough to spend meaningful time on the shop floor, in the data, and in front of users.

Requirements

  • 7–12 years of progressive experience in technology, operations, or strategy roles
  • Bachelor’s degree in engineering, computer science, operations research, industrial engineering, or a related technical field
  • Demonstrated success in operational improvement or transformation programs — Lean, Six Sigma, BPM, or equivalent with experience building business cases, measuring ROI, and sustaining adoption after implementation
  • Hands-on familiarity with modern AI/ML technologies, especially large language models (Claude, ChatGPT, Gemini) and their practical applications to business processes, including workflow automation, knowledge retrieval, decision support, and productivity improvement
  • Track record of leading teams of 2–5 people in cross-functional environments
  • Comfort and credibility across all levels of an industrial organization — from shop floor operators and department managers to BU executives

Nice To Haves

  • Prior experience as a or with Forward Deployed Engineers, applied AI engineers, or solutions architects at a leading AI or analytics company.
  • Manufacturing or industrial operations background — ideally aerospace, automotive, electronics, or fasteners - with exposure to commercial, engineering, quality, supply chain, or plant-floor workflows
  • Familiarity with ERP environments (SAP, Oracle, Epicor) sufficient to know where data lives and how to extract it
  • MBA, MS, or other advanced technical or business degree
  • Prior P&L responsibility, product ownership, or general management experience

Responsibilities

  • Own the BU’s AI roadmap, accountable to the BU President for measurable business impact across growth, margin, productivity, quality, speed, and decision-making
  • Lead the BU’s end-to-end process mapping effort — building the complete inventory of departmental processes that serves as the funnel for AI applications
  • Score and prioritize automation candidates by ROI, feasibility, adoption readiness, data availability, and business criticality; defend prioritization decisions to BU leadership
  • Recruit, manage, and develop a team of department-level Forward Deployed Engineers — initially 1–3 per BU onshore/offshore, scaling with demonstrated readiness
  • Build and deploy AI applications using Claude and other approved tools; design measurement frameworks to track impact per application, including baseline, expected benefit, user adoption, and realized business impact
  • Drive enterprise AI tool adoption across the BU; serve as the local champion and trainer
  • Partner with the central AI Enablement function (corporate IT) for tools, data access, vendor agreements, governance, cybersecurity, and responsible AI standards — escalating blockers through the company’s Unblock queue
  • Represent the BU in the company-wide AI Steering Committee on cross-BU patterns, shared learnings, and structural improvements
  • Track and report against KPIs: percent of BU processes mapped, percent automated by milestone, business impact per deployed application, adoption by target users, Finance-validated business impact, and scalability of deployed application
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