Principal Product Manager, AI Infrastructure

Full Job Description

Define and own the product vision, strategy, roadmap, and measurable outcomes for moving new AI capabilities from innovation to platform availability. Lead the end-to-end capability onboarding portfolio, from intake and requirements through packaging, launch, catalog distribution, lifecycle management, and transition to production adoption. Transform repeated launch activities, manual workflows, and bespoke integrations into reusable platform primitives, standardized contracts, automation, and self-service onboarding paths. Translate customer, partner, market, and business needs into clear product requirements, launch criteria, investment priorities, and portfolio tradeoffs across capability types and providers. Establish onboarding standards, decision rights, ownership boundaries, and handoff contracts across Product Management, Technical Program Management, Engineering, compliance, operations, and downstream product teams. Partner with Engineering on technical feasibility, architecture implications, reliability, and platform investments, and with TPM on integrated plans, dependencies, risks, governance, and launch readiness. Define and use outcome-based scorecards, including time to platform availability, onboarding throughput, launch success, standard-path adoption, capability reuse, and reduction in manual work, to guide investment decisions and continuously improve the onboarding system. Bachelor's Degree AND 8+ years experience in product/service/program management or software development OR equivalent experience. Bachelor's Degree AND 15+ years experience in product/service or software development OR equivalent experience. Demonstrated success owning product strategy for a technically complex platform, including defining the target customer, product value proposition, differentiated product direction, multi-year roadmap, and measurable business outcomes. Strong platform product management experience, including turning fragmented workflows, repeated integrations, or one-off launches into reusable product capabilities, common contracts, scalable services, automation, and self-service experiences. Technical depth in AI infrastructure, cloud platforms, distributed systems, developer platforms, or an adjacent domain, with the ability to engage credibly in architecture and feasibility discussions while maintaining clear accountability for the product's what, why, customer focus, and success measures. A record of leading consequential product decisions across multiple organizations using clear narratives, written strategy, evidence, decision frameworks, and executive communication to align senior product, engineering, and business stakeholders. Strong analytical product judgment, including experience defining outcome-based metrics, instrumenting customer and platform journeys, interpreting telemetry and qualitative feedback, and using evidence to improve product direction after launch.

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