Senior Product Manager - AI Foundation Team

Best Buy•Richfield, MN

4d•Hybrid

About The Position

As the Senior Product Manager for the AI Foundation Team, you will lead the engineering-focused roadmap of our AI scale hosting platform. The role owns the strategy for the backbone of our machine learning operations—from the AI Portal and SDKs used for experimentation to the massive-scale hosting infrastructure that serves our customers. This is not a typical product role; it requires a deep, authentic technical understanding of the ML lifecycle. It builds and enables the tools that empower our Data Scientists, ML Scientists, and Model Activation Engineers to build, deploy, and scale models efficiently. It sits at the intersection of complex infrastructure (Seldon, Kubernetes, GCP Vertex AI) and strategic business agility, driving the adoption of open-source models and next-gen AI capabilities. This role is hybrid, which means you will be required to work some days on-site at the Best Buy location listed on this posting and some days virtually from home or another non-Best Buy location. The specific work arrangements vary by role and team. The recruiter or hiring manager will provide more details during the hiring process.

Requirements

2+ years relevant product management experiences (dev, UX, strategy, etc.)
1+ direct team management/leadership/work direction
1+ years relevant experience in strategy creation, customer focused solutioning, cross-functional leadership, etc.
Bachelor's degree in IT, Computer Science, Engineering, Business, Marketing or related field OR equivalent combination of education and/or experiences
Experience with the Machine Learning Model Lifecycle (Training, Registry, Deployment, Serving, Monitoring).

Nice To Haves

Hands-on engineering experience with Google Cloud Platform
Experience launching platforms that support Open-Source Large Language Models (LLMs)
Strong technical fluency; ability to influence architectural trade-offs with engineering leads

Responsibilities

Lead the product strategy for a distributed AI Serving infrastructure
Drive the Agile delivery cadence, translating high-level strategic roadmaps into actionable user stories and prioritized backlogs for engineering execution
Proactively monitors the external technical landscape (AI Platform, GenAI, LLMs). Quickly processes new information to update plans and communicate shifts in strategy to stakeholders
Prioritizes work specifically for AI Platform engineers while balancing the distinct research priorities of Activation Engineers and Data\ML Scientists
Convey complex technical information clearly. Use storytelling to make the roadmap "real" for stakeholders, elevating their understanding of needs versus simple requests.