AI Digital Product Manager

Sherwin-Williams•Cleveland, OH

1d•Onsite

About The Position

At Sherwin-Williams, the AI Digital Product Manager leads the strategy, development, launch, and ongoing improvement of AI-powered digital products that help customers shop and connect with the company’s brands. The role is part of the Digital Products & Experience Design organization and identifies high-value customer needs, partnering with cross-functional teams to develop practical, scalable solutions. It owns the AI digital product roadmap and leads discovery, proofs of concept, and prototypes for web and mobile experiences across multiple brands. The role partners with data science, engineering, and UX teams to create intuitive AI-powered experiences that improve customer satisfaction and support retail growth. It works across consumer websites, mobile applications, and B2B digital platforms, applying AI where it delivers measurable value. Responsibilities span concept through launch and continued improvement, stakeholder alignment, digital product decisions, and measurement of business value. The position also conducts competitive and comparative audits and develops business cases for the company’s stage gate digital product investment process. The position is full-time in-office at Sherwin-Williams Headquarters in Cleveland, Ohio; it is not remote or hybrid. Travel is 10–20%. The role involves contact with employees and access to confidential or proprietary information and other items of value. Sherwin-Williams has determined that a criminal history review is necessary to protect its business, operations, reputation, staff, employees, and business relationships.

Requirements

Bachelor’s degree in business, marketing, computer science, information technology, or a related field, or equivalent experience. The posting states that candidates must have five years of work experience for every one year of college education required.
7–10 years of experience in digital product management, with demonstrated success defining and launching digital products or features; AI or data-driven product experience is ideal.
Ability to develop digital product strategy, conduct competitive analysis, write business cases, and navigate a stage gate or similar funding and approval process.
Experience leading cross-functional teams, including UX/design, engineering, and data science, to deliver digital products from concept through launch.
Understanding of AI and machine-learning concepts sufficient to evaluate use cases, collaborate with data scientists, and make informed product decisions.
Ability to prioritize across a complex digital product portfolio based on customer needs, business goals, and technical feasibility.
Strong communication and presentation skills, including demonstrated ability to align and influence executive-level stakeholders.
High integrity and professional judgment; strategic thinking; strong written and verbal communication; initiative and willingness to learn; flexibility; strong organization and deadline management; collaborative approach; and curiosity about digital innovation, customer experience, and responsible AI.

Nice To Haves

MBA or advanced degree focused on digital strategy, technology, product management, or data science.
Experience with AI-powered product features such as recommendation engines, personalization, search, computer vision, or conversational AI/chatbots.
Experience with B2C and B2B digital products in retail, e-commerce, or home improvement.
Familiarity with agile/Scrum delivery and experience partnering with digital product owners and delivery teams.
Experience with digital product discovery frameworks, design thinking, rapid prototyping, or proof-of-concept methods.
Working knowledge of digital analytics platforms such as Adobe Analytics or Google Analytics, and AI/ML experimentation frameworks such as A/B testing and feature flags.
Experience managing mobile application products for iOS and Android.
Proficiency with product management and collaboration tools such as Jira, Confluence, and Figma, or similar platforms.
Familiarity with generative AI tools and their use in customer-facing digital products.

Responsibilities

Define and own AI digital product strategy and a multi-horizon roadmap, identifying high-value AI and machine-learning use cases and balancing near-term results with long-term vision.
Conduct competitive and comparative audits to benchmark market leaders and identify innovation opportunities.
Develop and present business cases, including opportunity sizing, ROI analysis, and investment rationale, for stage gate funding and approval.
Champion human-centered design and represent digital product strategy to senior business stakeholders and executive leadership.
Oversee the digital product lifecycle from ideation, research, and validation through launch, optimization, and, where applicable, sunset.
Lead discovery, proofs of concept, prototypes, design sprints, and rapid prototyping for AI-powered web and mobile features across multiple brands.
Define product requirements, user stories, and acceptance criteria with UX, engineering, and data science teams.
Partner with digital product owners to translate strategic definitions into groomed backlogs and effective delivery by agile teams.
Manage releases end-to-end, coordinating technology, marketing, and business teams for go-to-market execution.
Establish product KPIs and measurement frameworks; oversee data acquisition, quality, integrity, and labeling requirements for AI model performance.
Use behavioral data, product analytics, model outputs, dashboards, and reporting to inform prioritization and continuous improvement.
Align business stakeholders, UX/design, data science, and technology teams; communicate product status, risks, and decisions across the organization.
Prepare presentations and recommendations for senior and executive stakeholders, and facilitate cross-functional workshops, sprint reviews, and roadmap planning.
Manage relationships with external vendors, agency partners, and technology providers to support delivery and quality.
Collaborate with data scientists and ML engineers to define AI model requirements, approaches, success criteria, governance, and monitoring.
Evaluate AI/ML approaches and tools, including generative AI, and recommend whether to build, buy, or partner.
Track traditional digital product KPIs such as engagement, conversion, retention, customer satisfaction, and revenue impact alongside AI metrics such as accuracy, precision, recall, latency, and bias indicators.
Build reporting cadences and executive dashboards, conduct post-launch reviews and retrospectives, and ensure improvements are tied to measurable business and customer value.
Stay current on AI/ML advancements and relevant applications in retail, e-commerce, and customer experience.