Product Manager, AI Recommendations & Intelligent Planning

Tempo

1d•Remote

About The Position

Tempo is seeking a Product Manager to lead the AI Recommendations Skill, a critical component of their Loop platform. This role involves operating at the intersection of AI systems, enterprise planning, and organizational decision-making. The Product Manager will be responsible for the full recommendation lifecycle, from signal ingestion to batch re-evaluation, ensuring that recommendations are actionable, trustworthy, and integrated into enterprise workflows. The ideal candidate will have experience in making AI/ML systems actionable within complex organizations and a deep understanding of enterprise planning processes and the factors that build trust in AI-generated guidance.

Requirements

3-5 years in a role responsible for making AI, data, or ML systems actionable inside complex organizations (e.g., consulting, decision intelligence, enterprise product management, strategic advisory).
Deep familiarity with enterprise planning decision-making processes, including authority, governance, and approval stages.
Experience with AI recommendation systems, rules engines, or decision automation.
Sophistication regarding AI recommendation trustworthiness: explainability, auditability, calibration, and organizational adoption of machine-generated guidance.
Fluency with concepts such as demand management, competitive intelligence, portfolio governance, scenario planning, and risk-adjusted prioritization.
Comfort using AI tools (e.g., LLMs) to accelerate product work.
Ability to manage systems complexity while focusing on the end-user experience.
Strong written communication skills for creating concise alignment documents.

Responsibilities

Develop and own the end-to-end product strategy and roadmap for Loop's Recommendations Skill.
Define and manage planning rules as a first-class product concept, including their definition, management, and versioning.
Design the recommendation surface to present prioritized, explainable recommendations to the right stakeholders at the right moment.
Develop governance and approval workflows for recommendations, ensuring efficient processing without bottlenecks.
Oversee the batch re-evaluation engine to ensure recommendations remain current with changing conditions.
Integrate competitive analysis into portfolio recommendations.
Conduct discovery with senior leaders (CSOs, portfolio leaders, PMO heads, enterprise architects) to understand strategic alignment needs.
Own, challenge, and evolve the AI recommendation engine model, including signals, insights, planning rules, competitive analysis, demand management, recommendations, governance, approval, and batch re-evaluation.