Principal Product Manager
Gigawatt AI
Principal Product Manager
Gigawatt AI
Modular AI OS for utility operations
Company Overview
Job Summary
We are seeking a Principal Product Manager for Gigawatt’s Customer team, the group building an AI-native customer platform with one goal: make the utility customer experience effortless. It replaces reactive, transactional, billing-centric systems with a proactive, omni-channel platform that treats the utility as a trusted advisor across web, mobile, and the call center.
You’ll own the transactional workflows behind those experiences: service orders, payments, and billing interactions. This is an early-stage role with a broad scope. You’ll define what customers and customer service representatives can do, how requests move through back-office systems, and what happens when a transaction fails or needs human intervention.
You’ll report to the Director, Customer and work closely with utility subject-matter experts, CX and call-center leaders, designers, and engineers. As the team grows, ownership may split into more focused areas; your initial mandate spans the he systems behind the customer experience from contact center to self service UX.
What you’ll own
This work has real consequences. A misapplied payment can create an incorrect past-due balance or put a customer’s service at risk. You’ll define requirements that account for these cases—not just the happy path—and make consequential system decisions understandable and auditable.
What you bring
Especially valuable: direct utility or utility-software experience; knowledge of payments
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Modular AI OS for utility operations
Gigawatt AI offers a modular AI operating system for utilities to modernize operations without replacing core infrastructure. It layers onto existing systems via a central Utility Data Fabric that unifies data across customer, revenue, operations, and compliance domains, with connectors and AI agent orchestration for automated workflows. It ships modular AI applications (Customer Module, Revenue Module) and uses a land-and-expand approach, often deploying in 30–90 days to demonstrate ROI with low risk. Its goal is to enable AI-powered modernization at a controlled pace, improving customer experience, financial operations, regulatory compliance, and grid intelligence.
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