Lead Product Manager - Agentic Foundations (P4476)

Lead Product Manager - Agentic Foundations; HM: Mark Roepke P4476

LOCATION: Cincinnati / Chicago

SUMMARY:

The AI Enablement team at 84.51° is seeking a Lead Product Manager for its Agentic Foundations team. This team is responsible for designing, developing, and maintaining the agentic backbone of the Kroger enterprise, including platforms, patterns, and tools to support the best practice development of AI agents.

The Lead Product Manager will discover, prioritize, plan the development of agentic capabilities and tooling - this could include agent/MCP/scorer/prompt registries, evaluation and monitoring tools, and low-code/no-code agent platforms. The role will partner closely with engineering and data science leads to shape the roadmap, translate business and technical needs into clear requirements, and ensure the delivery of high-value, enterprise-grade capabilities that reduce time-to-value, improve quality and reliability, and promote safe, compliant use of agentic systems.

RESPONSIBILITIES:

• Own product discovery and roadmap for products in the Agentic Foundations area

• Maintain a current roadmap and communicate trade-offs, dependencies, and timelines to stakeholders and delivery teams

• Translate business goals, user needs, and technical constraints into product requirements and acceptance criteria with a clear definition of done

• Partner with the Agentic Foundations leadership, as well as engineering and data science leads, to plan quarters/cycles/sprints and ensure efficient, predictable delivery

• Define and evolve core agentic capabilities, including:

• Registries (agent/MCP/scorer/prompt), templates, and pattern libraries

• Agent development and monitoring tools, including evaluation frameworks and observability

• Low-code/no-code agent platforms and SDKs/APIs/UIs that abstract complexity

• Integration with enterprise AIOps/MLOps, CI/CD, and governance workflows

• Facilitate user research and testing to understand developer and business user workflows; validate usability, safety, reliability, and performance

• Analyze product usage and operational data to inform prioritization, measure value, and guide iteration

• Drive adoption across customer teams through documentation, enablement, demos, and feedback loops; remove friction points and champion best practice

• Ensure alignment with enterprise strategies for scale, reliability, safety, compliance, and cost-efficiency

• Manage progress toward objectives; proactively surface risks, blocks, and cross-team dependencies; coordinate mitigation plans

• Develop strong internal and external stakeholder relationships; influence and drive change in ambiguous, evolving environments

• Communicate realized value and outcomes, including usage, adoption, productivity improvements, and risk reduction

QUALIFICATIONS, SKILLS, AND EXPERIENCE:

• Professional experience in agentic systems and platforms
• Professional experience in a product/software development team
• Professional experience in managing technical and business stakeholders
• Professional experience in ambiguous environments
• Skilled in a general technical acumen, able to efficiently converse with software engineers and AI engineers and understand their development processes
• Skilled in managing cross-functional technical development teams in an agile environment
• Skilled in managing business priorities against design/user needs while delivering against product roadmaps
• Skilled in managing end-to-end software product development
• Skilled in problem solving, analytic thinking, and creativity
• Skilled in planning, organization, and verbal/written business communication
• Skilled in maintaining a positive leader persona in ambiguous and changing environments
• Skilled in quickly flexing between technical and business stakeholder conversations, adapting to a variety of audiences
• Demonstrated excellence as a teammate and leader
• 4-6 years relevant experience
• Education: Bachelor's degree or higher in Software Engineering, Computer Science, Machine Learning, or a related field

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