Manager, AI Product Management at Prologis

San Francisco, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Logistics, Real Estate, Supply ChainIndustries

Requirements

Bachelor’s degree required
10+ years in product management, business analysis, consulting, or similar
3+ years leading multi-team initiatives or portfolios
Expert BPMN/process modeling and process redesign; strong workshop facilitation
AI literacy across document intelligence and agentic workflows: prompts & evaluation basics, retrieval concepts and strategies, tool/function calling, vector DB fundamentals, HITL design, and agent patterns
Product leadership: backlog & roadmap ownership, MVP scoping, vendor management, agile delivery, stakeholder communication & prioritization
Domain fluency in leasing/legal/doc-gen (contract templates & clauses, redlining/approval flows, repository, and retention)
Demonstrated ability to operate independently with initiative, influence diverse stakeholders

Responsibilities

Lead and mentor a team of IT Business Analysts, driving requirements gathering, process optimization, and solution alignment with business needs
Run discovery with business leaders/SMEs; map processes (BPMN 2.0) across the leasing lifecycle, legal, and doc generation/repository flows
Identify opportunities across three pillars: document intelligence, agentic workflow automation, and leasing sales AI
Build a KPI-tied and value measured AI use-case backlog; define a portfolio investment thesis and quarterly priorities
From BPMN flows, select the right agent architecture based on task structure, uncertainty, and control needs
Author conceptual designs: user journeys, prompt/pattern libraries, retrieval strategies, tool/API integrations (e.g., CRM, DRS, CLM, e-signature), HITL (human-in-the-loop) guardrails, acceptance criteria, risks, and evaluation plans
For leasing sales: design AI-assisted prospecting/qualification, outreach personalization, meeting/call summarization, next-best-action, and pipeline health insights
Present Problem Statement + Proposed Solution to Central AI for feasibility, standards, security, cost, and governance review; finalize scope (go/no-go)
Ensure initiatives adhere to platform/architecture standards and reuse components where possible
Act as Product Lead across multiple teams: roadmaps, backlogs, sprint goals, and SOWs; manage delivery risks and inter-domain dependencies
Coordinate data access and design with D&A/Tech BAs; ensure builds conform to enterprise standards and privacy/PII controls
Pilot, iterate, and scale; drive change management, training, and communications with Leasing/Legal/Doc Gen stakeholders
Monitor adoption, quality, cost, latency, and safety; own business value realization vs. plan
Capture and publish patterns/playbooks for cross-domain reuse; contribute requirements back to Central AI standards