AI Product Manager

Key Responsibilities

• Vision & Strategy: Own and define the product vision, strategy, and multi-release roadmaps tied to OKRs and value hypotheses.
• Operating Model: Establish the product operating model (discovery → build → adopt → operate) and set stage-gates and acceptance criteria.
• Technical Collaboration: Work with Architecture and Governance on patterns for RAG, agents, ML models, and integrations with ERP and AMOS applications.
• Commercial Ownership: Own business casing, pricing/benefit models, and post-launch value tracking; publish regular executive readouts.
  
• Execution Leadership: Lead backlog prioritization, release planning, and cross-vendor coordination while resolving impediments quickly.
• Responsible AI: Institutionalize Responsible AI and security-by-design in partnership with AI Security & Governance teams.
• Mentorship: Mentor PMs/POs and uplift general product management maturity across the organization.
• Portfolio Governance: Run a quarterly AI portfolio governance cadence with Business Teams and IBM to confirm value-stream prioritization, funding alignment, and roadmap trade-offs.

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  Operational Readiness: Define and enforce operational acceptance criteria (SLOs/SLA, monitoring, runbooks, access models, DR expectations) in partnership with Run & Operate teams before production go-live.
• Stage-Gate Decision Rights: Enforce explicit decision rights where the internal organization acts as the final approver at governance gates, while IBM remains accountable for delivery artefacts and evidence packs.

Minimum Qualifications

• Bachelor's or Master's degree in Engineering, Computer Science, or Business.
• 8–12 years in product management, with at least 5 years building AI/data products in enterprise contexts.
• PMP or PMI certified