Principal AI Product Manager

Astera Labs•San Jose, CA

About The Position

Astera Labs’ Applied AI team accelerates business outcomes through AI as the company scales. The Principal AI Product Manager sets direction and leads execution for AI-enabled products and workflows used across the business, connecting business priorities and user needs to product strategy and guiding cross-functional teams from opportunity discovery through delivery, adoption, and measurable results. This is a senior, hands-on product leadership role. The position leads discovery, prioritization, requirements, and execution across business and technical teams, while staying close to the technology to prototype, assess trade-offs, and guide responsible implementation. The focus is on scalable solutions to meaningful business problems. Success means establishing a focused, outcome-based roadmap that business leaders and delivery teams support; launching high-value AI solutions with strong adoption, responsible controls, and measurable impact; and building repeatable practices that help Applied AI scale its impact across Astera Labs.

Requirements

Bachelor’s degree in business, computer science, engineering, information systems, or a related field, or equivalent practical experience.
10+ years of relevant experience in product management, technology strategy, business transformation, enterprise systems, AI/automation, or a related discipline, including leadership of complex cross-functional initiatives.
Demonstrated success translating business needs into product strategy, prioritized roadmaps, clear requirements, and solutions that deliver measurable outcomes.
Experience working with senior stakeholders and diverse cross-functional teams, balancing business goals, user needs, technical constraints, and risk.
Practical experience with generative AI, enterprise AI products, workflow automation, or AI-enabled internal tools, and ability to evaluate when AI is or is not the right solution.
Technical fluency to collaborate credibly with engineering and IT teams, assess solution trade-offs, and prototype or test concepts using AI tools.
Strong business acumen and analytical skills, including defining success metrics and using data and user feedback to make prioritization decisions.
Strong organizational skills, including managing a portfolio of initiatives, dependencies, decisions, risks, and stakeholder follow-through.
Excellent written, verbal, and presentation skills, with a record of communicating complex topics clearly to technical and business audiences.
Strong judgment and experience incorporating privacy, security, responsible AI, and human oversight into product decisions.

Nice To Haves

MBA or advanced degree in a relevant technical or business field.
Experience leading AI product or internal AI transformation initiatives from discovery through production rollout and adoption.
Hands-on experience with Glean, Claude Code, LLM-based applications, AI agents, or workflow automation platforms.
Experience with product analytics, AI evaluation, experimentation, or measuring operational improvement.
Experience building AI capabilities or scalable internal products in a high-growth or rapidly evolving organization.

Responsibilities

Own the strategy, portfolio, and multi-quarter roadmap for Applied AI products and workflow solutions, aligned with company priorities and business outcomes.
Partner with business leaders and end users to identify high-value opportunities, understand workflows, quantify pain points, and validate product hypotheses.
Prioritize opportunities based on 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.
Use AI tools and rapid prototyping to test concepts and inform product decisions.
Set product quality and evaluation standards, 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 to support sustained adoption.
Embed privacy, security, responsible AI, access controls, and appropriate human oversight throughout discovery, design, development, and rollout.
Communicate product strategy, progress, risks, and recommendations to senior leaders and working teams, building alignment across differing priorities or perspectives.
Improve repeatable product practices for AI discovery, prioritization, evaluation, delivery, and adoption as the Applied AI function scales.