Senior AI Product Manager

The Senior AI Product Manager role is responsible for leading the development and launch of AI-enabled products, from conceptualization through proof of concept, pilot, scaled deployment, and continuous improvement, using agile methodologies and product operating model practices. The role reports to the AI Center of Excellence (COE) and works in close partnership with the Enterprise Technology Group (ETG). The incumbent has knowledge and experience in product management, AI/ML, data, and information technology principles, practices, and frameworks. In addition to defining product requirements and continuously refining the product strategy, the incumbent works closely with a cross-functional pod and key stakeholders across the organization, including business teams, technology product and platform owners, technical teams, and marketing teams, to build, deploy, and enhance AI-enabled products, including AI models, agents, data products, and applications. The incumbent supports the execution of AI-enabled products through design, proof of concept, MVP/pilot, and scaled deployment. Their responsibilities include ensuring adherence to product timelines, budgets, quality standards, responsible AI requirements, and customer needs. The incumbent contributes to a culture of collaboration, continuous improvement, and innovation within their team, driving the organization towards achieving its strategic objectives.

This position is not hybrid/remote and will be located at our Cleveland Headquarters office.

This position is not eligible for sponsorship for work authorization now or in the future, including conversion to H1-B visa.

Job duties include contact with other employees and access confidential and proprietary information and/or other items of value, and such access may be supervised or unsupervised. The Company therefore has determined that a review of criminal history is necessary to protect the business and its operations and reputation and is necessary to protect the safety of the Company’s staff, employees, and business relationships. 

Minimum Requirements:

• Bachelor's degree in Engineering, Computer Science, Data Science, Statistics, or Business Administration, or, in lieu of a degree, at least 7 years of experience in the field of technology product management 
• 4+ years of experience in technology product management with experience in launching and managing successful products at scale, including 2+ years managing production-grade AI/ML, data, or analytics products
• In-depth knowledge of product development and launch processes, including agile methodologies
• In-depth knowledge of product innovation methodologies and leading practices
• Ability to conduct market research and analyze customer needs, market trends, and competitive landscape
• Experience with AI/ML-enabled software product development, from proof of concept through scaled production deployment
• Knowledge of user experience (UX) design principles and customer-centric design thinking
• Knowledge of business processes, including IT, vendor management, software development lifecycle, and machine learning (MLOps) lifecycle
• Excellent communication skills and the ability to translate complex technical solutions into business language
• Working knowledge of AI/ML concepts, including predictive modeling, forecasting and optimization, generative AI, large language models, and agentic AI, sufficient to guide technical trade-offs with data science and engineering
• Knowledge of responsible AI principles, including bias, explainability, privacy, security, and human-in-the-loop design
• Proven ability to lead cross-functional pods without direct authority and to partner with Enterprise Technology on platform and architecture decisions
• Experience defining model evaluation, experimentation (e.g., A/B or test-versus-control), and business value measurement approaches, including defining baselines, hypotheses, and pre-agreed success thresholds
• Understanding of data management and data product principles, including data quality, governance, and semantic layers 
• Must be at least eighteen (18) years of age
• Must be legally authorized to work in the United States without sponsorship now or in the future for employment visa status

Preferred Qualifications:

• Agile product management certification (e.g., PMI-ACP, SAFe POPM, PMC, CSPO)
• Master’s degree in a quantitative or technical field, or MBA
• AI/ML or data platform certification (e.g., Databricks, Microsoft Azure AI)

Technical/Skill Requirements:

• Agile Software Development Lifecycle (SDLC) and AI/ML Lifecycle (MLOps) Methodologies
• Agile Project Management Tools (e.g., Jira, Confluence, Azure DevOps)
• Product Analytics & BI Tools, including SQL (e.g., Power BI, Databricks SQL)
• Customer Relationship Management
• Market Research & Competitive Analysis
• Product Strategy & Planning
• Product Risk Management
• Modern Delivery
• Product Lifecycle Management
• Demand & Capacity Management
• Technology Domain Knowledge
• Product Optimization & Growth Strategy Development
• Product Requirements Gathering & Documentation
• Persona Creation & Journey Mapping
• Reporting Tools
• AI-Assisted Development Tools (e.g., GitHub Copilot)
• Microsoft 365 & Power Platform
• Responsible AI & AI Risk Management
• Data & AI Platforms (e.g., Databricks, Microsoft Azure AI / Azure OpenAI, Microsoft Copilot Studio)
• AI/ML Model Evaluation & Experimentation
• Generative & Agentic AI Solution Design
• Data Product Design & Data Governance

Travel Requirements

• 5%

• Develop and execute product strategy, including product roadmaps, priorities, release plans, budgeting, value case, positioning, and messaging​
• Define product requirements in partnership with the business and work with cross-functional teams (engineering, design, sales, marketing, etc.) to ensure product vision is well understood and executed​
• Conduct user and market research and analysis to identify end-user needs, market trends, competitive threats​, and emerging AI/ML capabilities
• Define, track, and report on business value, adoption, and model performance metrics — including value realized, sustained adoption, time or cost saved, model quality, and cost per transaction or per use — against baselines and pre-agreed success thresholds defined before pilot, to measure success and recommend ship, iterate, or stop decisions and adjust strategy as needed
• Shape and prioritize the product backlog utilizing business expertise, understanding of customer needs, and consideration of business value vs. effort to develop, including continuous experimentation after launch
• Manage the AI product development lifecycle, from concept through proof of concept, MVP/pilot, and scaled deployment, ensuring products are delivered on time, on budget, and meet quality and Responsible AI standards​
• Own and manage knowledge documentation in support of the product ​
• Communicate product updates and progress to stakeholders and executive leadership, including translating technical concepts to non-technical stakeholders​
• Build and maintain effective working relationships with internal and external stakeholders​
• Analyze product performance, model performance, user adoption, and customer feedback to identify areas for improvement and drive continuous product innovation, including ongoing experimentation after launch
• Partner with data science and ML engineering to frame business problems as AI/ML use cases, define baselines, hypotheses, model evaluation criteria and acceptance thresholds, and design experimentation (including A/B or test-versus-control, and causal inference where randomization is not possible) and instrumentation to measure business value, and make informed trade-offs among accuracy, explainability, cost, and latency
• Partner with technology team to industrialize AI-enabled products on enterprise data and AI platforms (e.g., Databricks, Microsoft Azure), including MLOps, monitoring, drift detection, retraining triggers, post-launch evaluation, incident response, inference / token / compute cost management, and transition to run operations
• Ensure AI-enabled products comply with AI COE responsible AI, data privacy, security, and AI governance standards, including risk tiering, evaluation and red-teaming before scale, human-in-the-loop design, and a go / no-go recommendation with Legal, Privacy, and Cybersecurity, and risk mitigation
• Define and enforce data requirements for AI-enabled products, including data quality, lineage, and semantic layer standards for AI models, agents, and data products
• Define agentic AI product requirements, including autonomy levels, tool use, guardrails, and agent-specific evaluation, for AI agents deployed to end users
• Drive end-user adoption and change management in partnership with business leaders, including training, process redesign, and feedback loops 

Salary Frequency: Annually

Minimum Salary: 108,531.02

Maximum Salary: 140,086.17