The posting, in Astera Labs's own words
archived Nov 3, 2026Astera Labs (NASDAQ: ALAB) provides rack-scale AI infrastructure through purpose-built connectivity solutions. By collaborating with hyperscalers and ecosystem partners, Astera Labs enables organizations to unlock the full potential of modern AI. Astera Labs’ Intelligent Connectivity Platform integrates CXL®, Ethernet, NVLink, PCIe®, and UALink™ semiconductor-based technologies with the company’s COSMOS software suite to unify diverse components into cohesive, flexible systems that deliver end-to-end scale-up, and scale-out connectivity. The company’s custom connectivity solutions business complements its standards-based portfolio, enabling customers to deploy tailored architectures to meet their unique infrastructure requirements. Discover more at www.asteralabs.com .
About the role
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.
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What you’ll do
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, , 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.