Interested in this AI Product Manager role at KeyBank?
Apply Now →Skills & Technologies
About This Role
Location:
4910 Tiedeman Road, Brooklyn OhioJob Summary
The Enterprise GenAI Product Manager coordinates product strategy, discovery, requirements, product design, and roadmap planning for KeyBank’s portfolio of centrally supported Generative AI platforms, tools, and shared capabilities.
The role partners with Lines of Business, Shared Services, end users, governance partners, and technology teams to identify common needs and translate recurring demand into product concepts, user experiences, requirements, and roadmap priorities. This includes leading the product design and evolution of the AI Marketplace and related experiences that help employees discover, access, and use approved AI capabilities.
Serving as a central organizing point across existing and emerging enterprise GenAI capabilities, the Product Manager maintains an integrated view of how those capabilities work together, the needs they address, where they overlap, where gaps remain, and the support required for responsible adoption and growth. The role evaluates emerging tools and platform capabilities based on their potential value to KeyBank, intended users, access models, enterprise fit, and alignment with Key’s governance expectations and risk appetite.
The Product Manager partners with the GenAI Platform Engineering team, Microsoft and Google platform teams, Architecture, Governance, Risk, Information Security, and other stakeholders to move approved product concepts from discovery through design, build, launch, and ongoing enhancement.
Essential Functions
- Lead product discovery with Lines of Business, Shared Services, end users, capability owners, and governance and technology partners to identify recurring demand, common enterprise needs, and opportunities for centrally supported capabilities.
- Translate stakeholder needs and portfolio insights into product concepts, user journeys, business and functional requirements, experience designs, acceptance criteria, and prioritized roadmaps.
- Lead the product design and evolution of the AI Marketplace, enterprise prompt resources, capability catalogs, and other centrally supported GenAI products and experiences.
- Partner with the GenAI Platform Engineering team and other technical teams to translate approved product concepts and requirements into delivered capabilities through design, development, testing, release, and ongoing enhancement.
- Lead business exploration of emerging GenAI products and capabilities, including Microsoft Copilot, Copilot Studio LE, Agent Builder, Gemini Enterprise, Scout, evaluation platforms, and future enterprise AI offerings.
- Maintain an integrated view of the enterprise GenAI product portfolio, evaluating how platforms and capabilities interact, where they overlap, where gaps remain, and where expansion, integration, consolidation, replacement, retirement, or additional investment should be considered.
- Develop recommendations regarding product positioning, intended users, access models, priority use cases, product boundaries, rollout approaches, and readiness conditions for centrally supported GenAI tools and services.
- Evaluate proposed products and significant enhancements for employee value, enterprise fit, usability, scalability, support requirements, organizational readiness, governance and risk considerations, and compatibility with Key’s risk appetite.
- Develop business cases, product recommendations, options analyses, roadmap updates, and executive decision materials for enterprise GenAI product and capability decisions.
- Maintain current product information, including purpose, scope, target users, available capabilities, limitations, requirements, roadmap, dependencies, access and support models, ownership, and release-readiness considerations.
- Define measures of adoption, coverage, readiness, value, user experience, and capability maturity with platform, portfolio, and reporting partners. Use research, feedback, pilots, demand patterns, usage information, and platform insights to guide product enhancements.
- Coordinate product roadmaps, dependencies, handoffs, and readiness activities across Platform Engineering, Governance, Risk, Architecture, Communications & Enablement, Learning, Support, Finance, and platform-owner teams.
- Support product lifecycle decisions involving the introduction, expansion, integration, consolidation, replacement, or retirement of enterprise GenAI capabilities. Serve as a knowledgeable point of coordination for current and planned enterprise GenAI products.
- Perform other duties as assigned; duties, responsibilities, and/or activities may change or new ones may be assigned at any time with or without notice.
- Comply with all KeyBank policies and procedures, including without limitation acting professionally at all times, conducting business ethically, avoiding conflicts of interest, and acting in the best interests of Key’s clients and Key.
Education
- Bachelor’s degree in Business, Technology, Information Systems, Engineering, Product Design, or a related field, or equivalent experience.
Work Experience
- Eight or more years of experience in product management, business analysis, platform strategy, product design, technology strategy, or a related discipline.
- Experience leading product discovery and translating stakeholder needs into product requirements, user experiences, roadmaps, and solution recommendations.
- Experience designing and evolving technology products, platforms, marketplaces, catalogs, shared services, or comparable enterprise experiences.
- Experience partnering with engineering, architecture, platform, business, and control teams throughout product design, development, release, and enhancement.
- Experience evaluating emerging technologies for enterprise value, usability, readiness, scalability, and risk.
- Experience developing business cases, product recommendations, roadmap materials, and executive decision content.
- Experience with Generative AI, emerging technology, or regulated industries preferred.
Skills
- Product discovery and stakeholder engagement.
- Product strategy and roadmap planning.
- Business and functional requirements definition.
- Product design and user experience development.
- Enterprise platform and capability evaluation.
- Product portfolio positioning and lifecycle planning.
- Business case development and decision analysis.
- Analytical problem-solving and data-informed decision-making.
- Executive communication and stakeholder influence.
- Business and technical fluency.
Core Competencies
- Product Management
- Business Analysis
- Product Discovery
- Product Design
- Strategic Thinking
- User Experience Orientation
- Stakeholder Management
- Cross-Functional Collaboration
All KeyBank employees are expected to demonstrate Key’s Values and abide by Key’s Code of Conduct.
Physical Demands
- General Office: Prolonged sitting, ability to communicate face to face in person or on the phone with teammates and stakeholders, frequent use of a PC or laptop, and occasional lifting, pushing, or pulling of backpacks or computer bags up to 10 pounds.
Work Location Category
- Hybrid (2+ days)
COMPENSATION AND BENEFITS
This position is eligible to earn a base salary in the range of $80,000.00 - $150,000.00 annually. Placement within the pay range may differ based upon various factors, including but not limited to skills, experience and geographic location. Compensation for this role also includes eligibility for incentive compensation which may include production, commission, and/or discretionary incentives. Please click here for a list of benefits for which this position is eligible.
Key has implemented an approach to employee workspaces which prioritizes in-office presence, while providing flexible options in circumstances where roles can be performed effectively in a mobile environment.
Job Posting Expiration Date: 10/31/2026 KeyCorp is an Equal Opportunity Employer committed to sustaining an inclusive culture. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, pregnancy, disability, veteran status or any other characteristic protected by law. Qualified individuals with disabilities or disabled veterans who are unable or limited in their ability to apply on this site may request reasonable accommodations by emailing [email protected].
#LI-Hybrid
Salary Context
This $80K-$150K range is in the lower quartile for AI Product Manager roles in our dataset (median: $193K across 99 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 9,653 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At KeyBank, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $220,200 based on 862 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($115K) sits 48% below the category median. Disclosed range: $80K to $150K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
KeyBank AI Hiring
KeyBank has 2 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer. Positions span Brooklyn, OH, US, New York, NY, US. Compensation range: $150K - $181K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.