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.
