Lead Product Manager - AI Platforms Kroger Precision Marketing (P898)

8451; Cincinnati (OH); On-site; USD 120,000 - 160,000; Full time

Job summary

84.51° is seeking a Senior Product Manager to lead the AI Platform domain, owning the roadmap and aligning Data Science and Engineering to build reusable services for Kroger Precision Marketing.

The role focuses on reducing time and cost to create new AI capabilities, partnering with others, and delivering across platforms. This is an in-office Cincinnati role with collaboration across teams.

Qualifications

• 3–5 years of product management experience.
• Strong understanding of how LLM-powered and agentic products move from prototype to production, including prompt and context design, RAG, orchestration, tool integration, evaluation frameworks, LLM observability, feedback loops, governance, and rollout.
• Experience building shared platforms, internal developer tools, or reusable capabilities where product and engineering teams are the primary customers.

Responsibilities

• Own the platform roadmap: translate the AI Platform vision into a clear roadmap and sequence foundational capabilities.
• Scale reusable AI foundations: own shared agent infrastructure, context-layer capabilities, deployment patterns, tooling, and standards.
• Know your builders: partner with product and agent builders to understand blockers and needs.
• Pick the right bets: identify high-leverage investments and drive adoption, reuse, and impact.
• Lead with market-informed judgment: stay current on AI trends and competitors; adjust approach with evidence.

Skills

Product management

GenAI product delivery

Platform and builder mindset

Stak

Job description

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 at 84.51°!

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 at scale. The 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. The 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 measures, agent quality evaluations, observability signals, and feedback loops that improve reliability, adoption, and business impact


• Enable the organization: educate teams on the platform, how to use it, and where it is going; rally stakeholders around the shared vision; and create the forums, documentation, and lightweight processes that help builders adopt the platform consistently


• Communicate clearly and build trust: communicate plans, progress, tradeoffs, risks, and decisions with clarity; raise issues early with context and options; and earn trust through strong follow-through and reliable decision-making

Minimum Qualifications

• Product management: 3-5 years of product management experience


• GenAI product delivery and quality: strong understanding of how LLM-powered and agentic products move from prototype to production, including prompt and context design, RAG, orchestration, tool integration, evaluation frameworks, LLM observability, feedback loops, governance, and rollout


• Platform and builder mindset: experience building shared platforms, internal developer tools, or reusable capabilities where product and engineering teams are the primary customers


• Stak