Principal AI Product Manager

Principal AI Product Manager:

Astera Labs’ Applied AI team works to accelerate business outcomes through the use of AI as the company scales. We’re seeking a Principal AI Product Manager to set direction and lead execution for AI-enabled products and workflows used across the business. You’ll connect business priorities and user needs to a clear product strategy, then guide cross-functional teams from opportunity discovery through delivery, adoption, and measurable results.

This is a senior, hands-on product leadership role. You’ll lead discovery, prioritization, requirements, and execution across business and technical teams, while staying close enough to the technology to prototype, assess trade-offs, and guide responsible implementation. The focus is on creating scalable solutions that solve meaningful business problems—not deploying AI for its own sake.

• Own the strategy, portfolio, and multi-quarter roadmap for Applied AI products and workflow solutions, aligned to company priorities and business outcomes.
• Partner with business leaders and end users to identify high-value opportunities, understand current workflows, quantify pain points, and validate product hypotheses.
• Prioritize opportunities using a clear framework that considers user value, business impact, feasibility, risk, dependencies, scalability, and time to value.
• Translate needs into product vision, requirements, user journeys, success measures, and appropriately scoped delivery plans.
• Lead cross-functional execution with Applied AI, engineering, IT, security, data, and business partners; align owners, decisions, dependencies, milestones, and trade-offs.
• Stay hands-on with AI tools and rapid prototyping, using platforms such as Glean, Claude Code, and approved automation tools to test concepts and inform product decisions.
• Set standards for product quality and evaluation, including accuracy, reliability, user experience, adoption, and human review where appropriate.
• Establish and track outcomes such as adoption, time saved, cycle-time reduction, quality, user satisfaction, and business impact; use results to refine roadmaps and investment choices.
• Guide launch, change management, enablement, documentation, and feedback loops so solutions are adopted and sustained.
• Embed privacy, security, responsible AI, access controls, and appropriate human oversight throughout discovery, design, development, and rollout.
• Communicate product strategy, progress, risks, and recommendations clearly to senior leaders and working teams; build alignment when priorities or perspectives differ.
• Improve repeatable product practices for AI discovery, prioritization, evaluation, delivery, and adoption as the Applied AI function scales.

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