Product Management Lead

Honeywell Honeywell · Industrial · Raleigh, NC +1

Product Management Lead for Honeywell Forge cloud-hosted applications for utilities, focusing on integrating AI capabilities into utility workflows. The role involves defining product strategy, requirements, and roadmaps for AI features, translating AI capabilities into business value, and partnering with engineering to ship AI-powered products.

What you'd actually do

  1. Define product requirements, specifications, and roadmap for applications in the Forge Utility Software portfolio. Maintain alignment with the broader Forge platform architecture.
  2. Own the product strategy for AI features across the portfolio, including AI for grid operations, DER management, rate design, and utility program performance. Translate AI capability into utility-relevant outcomes.
  3. Work with Solution Architects, Sales, and customers to identify the highest-value use cases. Conduct VOC and competitive analysis, especially against utility analytics and DERMS competitors.
  4. Set product requirements and feed development priorities into the engineering / R&D organization.

Skills

Required

  • 6+ years of experience.
  • Cloud software product management experience.
  • AI / ML product fluency.
  • Utility domain knowledge.
  • Market-back product methodology.

Nice to have

  • Experience with utility data integration platforms (head-end systems, MDMS, data lakes, or similar).
  • Experience defining commercial models for AI features (consumption-based pricing, tiered SaaS, etc.).
  • Background working with utility regulators, EPRI, or industry consortia.

What the JD emphasized

  • AI / ML product fluency
  • Working knowledge of how to scope, evaluate, and ship AI features in a B2B context.
  • Understand the difference between an AI demo and an AI product, and can pressure-test feasibility, accuracy thresholds, and deployment risk with engineers.

Other signals

  • AI capabilities for utilities
  • AI features across the portfolio
  • Translate AI capability into utility-relevant outcomes
  • AI / ML product fluency
  • ship AI features in a B2B context