Principal Product Manager

Title: Principal Product Manager
Location: Remote or San Francisco, CA

Our Intelligence Platform powers the AI-driven experiences that millions of customers interact with every day across digital and voice channels. We are building the next generation of customer-facing AI agents that can do more than follow scripts. They need to understand context, reason through problems, and take action on behalf of customers. The platform also includes our Agent Marketplace, a composable library of production-ready AI skills that accelerates how quickly we can stand up new AI-powered programs. This is one of the highest-impact product areas in the company, and we are looking for someone who wants to help shape it. This work will deliver on Asurion’s promise to deliver the highest level of technology care across consumers technology lifecycle.

As a Principal Product Manager you will join the Intelligence Platform team and own the strategy, development, and performance of our customer-facing AI agents and our Agent Marketplace. You will sit at the intersection of product management and data science, focused on building AI-powered experiences across the full lifecycle care journey while driving the composable platform that makes every AI investment reusable across the organization.

You will partner directly with our Data Science team to advance the capabilities of our AI agents, working alongside Engineering, Design, Care Operations, and business stakeholders. This is a hands-on product role where you will shape how our AI agents interact with customers, help move us toward a more agentic approach where AI can reason, plan, and act on behalf of customers, and drive the marketplace strategy that accelerates delivery of new AI-powered programs from weeks to days.

Key Responsibilities:

AI Agent Strategy & Roadmap

• Own the product vision, strategy, and roadmap for customer-facing AI agents across digital (chat, messaging, app) and voice (IVR, voice assistant) channels.

• Proactively shape the roadmap to move from scripted automation toward agentic experiences that can reason, plan, and take action, improving resolution rates and reducing customer effort.

• Define and track success metrics that tie AI agent performance to measurable outcomes: resolution rate, customer satisfaction, containment, handle time reduction, and self-service coverage.

• Evaluate emerging AI capabilities (large language models, multi-modal AI, tool use, memory, retrieval-augmented generation) and make clear recommendations on what to adopt and when.

• Understand the pulse of the business and anticipate what our AI agents need to do next, not just what they do today.

Data Science Partnership

• Serve as the primary product partner to the Data Science team, co-developing the AI capabilities that power our customer-facing agents.

• Translate business needs and customer pain points into clear problem statements that data scientists can build against, with well-defined success criteria.

• Engage in technical trade-off conversations around model architectures, training approaches, prompt engineering, and evaluation methods.

• Partner on experimentation strategy, A/B testing frameworks, and model performance benchmarking to continuously improve agent quality and expand coverage.

Lifecycle Care Journey

• Map AI agent capabilities across the full customer lifecycle (onboarding, troubleshooting, claims, upgrades, retention) and prioritize the opportunities with the greatest customer and business impact.

• Drive a cohesive cross-channel experience so customers get consistent, intelligent support whether they engage via chat, voice, or self-service.

• Collaborate with Care, Operations, and CX teams to understand frontline realities and make sure AI agents complement human experts rather than creating friction.

Cross-Functional Execution

• Work across Engineering, Design, Data Science, Care Operations, and business stakeholders to ship AI-powered experiences at pace.

• Influence leadership on where to invest in AI capabilities and how to sequence bets for maximum return across the Intelligence Platform.

• Drive alignment between business objectives and technical feasibility, managing trade-offs with transparency.

• Champion a culture of rapid experimentation, learning from failures, and iterating quickly.

Agent Marketplace

• Own the product strategy and roadmap for the Agent Marketplace, a composable platform of production-ready AI skills that enables teams to discover, reuse, and assemble capabilities across domains.

• Drive adoption across