AI Product Manager
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Responsibilities
- AI Product Strategy & Innovation
- Identify, evaluate, and prioritize AI and automation opportunities across enterprise platforms and business processes.
- Define product vision, outcomes, and roadmap aligned to business priorities and platform strategy.
- Assess platform-native AI capabilities versus custom-built solutions to maximize value, speed, and scalability.
- Product Lifecycle Management
- Own the full product lifecycle from ideation through delivery, adoption, continuous improvement, and end-of-life planning.
- Translate strategy into clear product requirements, user stories, acceptance criteria, and a well-managed backlog.
- Drive product operating rhythms including sprint readiness, prioritization, release planning, and measurable outcomes.
- Cross-Functional Leadership & Stakeholder Management
- Partner closely with platform engineering, architecture, security, operations, and business stakeholders to deliver value at enterprise scale.
- Provide clear communication on product direction, tradeoffs, milestones, risks, and outcomes to senior stakeholders.
- AI Governance, Responsible AI & Risk Management
- Ensure AI products align to responsible AI principles and enterprise expectations for compliance, security, and privacy.
- Contribute to governance practices that reduce risk (e.g., model behavior, data exposure, operational controls) while enabling innovation at speed.
- Metrics, Adoption & Value Realization
- Define success metrics and drive adoption through iterative enhancements, stakeholder enablement, and outcomes tracking.
- Track and report product performance indicators to guide prioritization and future roadmap decisions.
- Required Qualifications
- Bachelor's degree in Business, Engineering, Computer Science, Data Science or related field
- 7-10+ years of experience in Product Management, Digital Transformation, or Enterprise Platforms
- Significant experience in product management across digital/software products, with demonstrated exposure to AI/ML or GenAI concepts and use cases .
- Strong product fundamentals: discovery, requirements definition, prioritization, backlog hygiene, and release execution.
- Demonstrated ability to influence and align cross-functional stakeholders in a matrixed enterprise environment.
- Curiosity and learning agility: strong ability to learn new domains quickly, ask incisive questions, and turn ambiguity into product clarity.
Requirements
- Technical background in software engineering, data, or applied AI/ML; ability to engage with engineering teams on feasibility, architecture considerations, and delivery tradeoffs.
- Experience with LLMs, prompt engineering, and responsible AI practices.
- Exposure to GenAI platforms and cloud AI services (e.g., Azure AI and similar).
- Experience with AI deployment patterns, or scaling AI solutions across large organizations
- Experience building AI-powered products or intelligent automation solutions
- Product management and AI related certification is a plus
- Knowledge, Skills, and Competencies
- Product strategy and roadmap ownership; ability to connect product decisions to measurable business outcomes.
- Strong written and verbal communication, including executive-ready storytelling and business case development.
- Structured problem-solving, prioritization discipline, and bias for execution.
- Strong collaboration and leadership in cross-functional product operating models.
- Pay & Benefits
- The pay range for this role is $116,150 to $182,400 USD annually with additional
- opportunities for pay in the form of bonus and/or equity (applies to United
- States of America candidates only). Pay varies by work location, job-related
- knowledge, skills, and experience.
Benefits
Additional Information
AI Product Manager Description - Job Summary / Position Overview HP is seeking an AI Product Manager to define, build, and scale AI-driven products and capabilities across our enterprise platform landscape (e.g., SAP, ServiceNow, MuleSoft, Adobe Commerce, and automation platforms). This role is accountable for end-to-end product ownership , including opportunity identification, product strategy, roadmap development, requirements definition, backlog management, delivery partnership with engineering, and ongoing adoption and optimization. The ideal candidate brings a strong learning mindset and curiosity , practical familiarity with AI product management , and a technical foundation enabling effective partnership with engineering and architecture teams.
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Company Intel
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