Staff AI Product Solutions Manager (Remote)

About the Role

As a Staff AI Product Solutions Manager, you will identify, shape, and advance domain and enterprise AI opportunities that deliver measurable business value for Kohl’s. You will work across technology, architecture, business, risk, and delivery teams to assess where AI can solve meaningful problems and determine the best path to bring those capabilities to life.

This role focuses on the front end of the AI lifecycle and acts as a strategic value orchestrator and context engineer: evaluating opportunities, defining use cases and guardrails, validating value through rapid experimentation, and translating proven patterns (including headless AI architecture patterns) into clear direction for teams that will implement, scale and maintain them across the enterprise.

What You’ll Do

• Partner with business and technology leaders to identify, assess, and prioritize AI opportunities based on business value, feasibility, risk, and organizational readiness
• Define AI use cases, target outcomes, success measures, user needs, and adoption considerations for enterprise AI capabilities
• Lead discovery and rapid experimentation, including use of synthetic user personas and simulation environments, to validate user value, model performance, technical feasibility, and cost-to-serve before broader investment or scale
• Drive build-versus-buy assessments for AI capabilities, platforms, open-weights models, commercial foundation models vs. fine-tuning in-house Small Language Models (SLMs)), and vendor solutions in partnership with Enterprise Architecture, Engineering, Procurement, Legal, and Security
• Establish product direction for probabilistic and agentic experiences, including appropriate guardrails, human-in-the-loop workflows, escalation paths, and acceptable performance thresholds
• Author natural-language “context Specs”, “agent playbooks”, and manage “probabilistic tolerances” for multi-agant systems and workflows
• Translate validated AI solutions into capability briefs, reusable patterns, and implementation guidance that enable delivery teams to scale solutions consistently
• Partner with delivery, change management, and business teams to develop adoption plans and ensure AI capabilities are embedded into workflows in ways that drive measurable outcomes
• Define and monitor value, quality, risk, and cost metrics (establishing unit economics of compute, evaluating token costs and balancing model accuracy with latency); use insights to recommend whether to scale, refine, pause, or retire AI solutions
• Communicate complex AI concepts, tradeoffs, recommendations, and outcomes clearly to executive and cross-functional stakeholders
• Provide thought leadership on emerging AI capabilities, practices, and responsible adoption across the enterprise
• Additional tasks may be assigned

What Skills You Have

Required

• Bachelor’s degree in Business, Technology, Data/Analytics, Computer Science, or related field; equivalent experience considered 
• 7+ years of experience in product strategy, managing concurrent product portfolios, digital transformation, technology, or related work
• 3+ years leading AI, machine learning, data platform, or other complex technology initiatives 
• Experience taking AI or technology opportunities from discovery through implementation and measurement 
• Knowledge of modern AI concepts, including Large Language Models (LLMs), retrieval-augmented generation (RAG), model evaluation, and non-deterministic systems 
• Experience assessing value, feasibility, risk, and investment tradeoffs across cross-functional partners 
• Experience using business, product, operational, or financial metrics to guide decisions

Preferred

• Advanced degree, certification, or training in a relevant business or technical discipline 
• Experience with AI vendor evaluation and build-versus-buy decisions 
• Familiarity with AI architecture and tooling, such as vector databases, agent orchestration, or Model Context Protocol (MCP) and tool-calling interfaces 
• Experience in a centralized AI, hub-and-spoke, or center-of-excellence model 
• Experience managing AI platform, compute, inference, or vendor costs