AI Product Manager
Skills
About This Role
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.
- **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
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