Lead Product Manager - AI Platforms Kroger Precision Marketing; P989

Position: Lead Product Manager - AI Platforms Kroger Precision Marketing (P989)
84.51 Overview:
84.51 is a retail data science, insights and media company. We help The Kroger Co., consumer packaged goods companies, agencies, publishers and affiliates create more personalized and valuable experiences for shoppers across the path to purchase.

Powered by cutting-edge science, we utilize first-party retail data from more than 62 million U.S. households sourced through the Kroger Plus loyalty card program to fuel a more customer-centric journey using 84.51 Insights, 84.51 Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.
84.51 follows a 5‑day in‑office work schedule to support collaboration, alignment, and team connection.

Join us !__________________________________________________________84.51 is a retail data science, insights, and media company that helps brands grow by delivering smarter, more accountable marketing powered by Kroger’s first-party data. Kroger Precision Marketing (KPM) is our commercial arm, enabling brands to connect with customers through insights, incentives, and media.

Role Summary Kroger Precision Marketing (KPM) has launched an AI Platform domain to define how AI is built, scaled, and used across internal teams and external brand-facing platforms.

This Senior Product Manager role leads a cross-functional team across Data Science and Engineering and owns the roadmap for the shared foundation that helps KPM teams build trusted agents  north star for this foundation is to reduce the time and cost of building new AI capabilities by turning common infrastructure, context, tooling, and governance into reusable platform services. This foundation is what makes a unified KPM AI experience possible — one assistant, across every platform, workflow, and team, built once and delivered everywhere.

The work spans two layers. The infrastructure layer includes enterprise agent development and deployment patterns, shared chat and notification experiences, Agent-to-Agent (A2A) interactions, and Model Context Protocol (MCP) infrastructure. The intelligence and quality layer includes context-layer capabilities, agent reasoning and evaluation, LLM observability, feedback loop design, product analytics, and governance.

The role partners with the AI Platform Director to connect these capabilities to the broader domain vision while creating practical, reusable platform services that teams can build on without reinventing the same foundations.

Key Responsibilities Own the platform roadmap: translate the AI Platform vision into a clear roadmap, proactively define plans to move the work forward, and sequence foundational capabilities based on customer needs, business value, technical readiness, risk, cost, and reuse potential

Scale reusable AI foundations: own shared agent infrastructure, context-layer capabilities, deployment patterns, tooling, and standards that help teams build new AI capabilities faster without duplicating platform wiring

Know your builders: partner with product and agent builders to understand how they work, where they are blocked, and what shared capabilities would unlock the most value across the portfolio

Pick the right bets: identify the highest-leverage platform investments, make explicit tradeoffs, and focus the team on the capabilities that unlock the most reuse, adoption, and downstream product impact

Lead with market-informed judgment: stay current on AI trends, vendors, and competitor moves; form a clear point of view; seek input early; and adjust quickly when evidence points to a better approach

Ship with momentum: drive delivery with Agile Delivery, Data Science, and Engineering by managing scope, dependencies, risks, tradeoffs, and timelines

Drive adoption, quality, and impact: define rollout plans, success…