Senior Product Manager, AI

Responsibilities

• Own the product vision, strategy, and roadmap for agentic AI solutions that reduce out-of-stocks, shrink and waste, and improve fulfillment utilization for retailers and CPGs.
• Work backwards from customer outcomes to write crisp problem statements, PRDs, and success metrics; prioritize ruthlessly to deliver v0, iterate to v1, and scale proven features.
• Partner with engineering and data science to scope experiments, manage backlogs, define KPIs and evaluation frameworks, and ensure models and agents are reliable, safe, and observable.
• Lead discovery with customers; design pilots and proof points; collaborate with sales and marketing on go-to-market, pricing and packaging, enablement, and case studies that drive revenue.
• Own the business case: model unit economics and ROI, set financial targets for margin recovery/efficiency, and report performance to executives and external stakeholders.
• Ensure data readiness and integrity by assessing data quality, telemetry, integrations, and feedback loops; implement human-in-the-loop and policy guardrails where appropriate.
• Operate cross-functionally with data engineering, retailer success, enterprise sales, and BD to bring products from concept to launch and expansion.

Requirements

• 6+ years of product management experience building B2B or enterprise software, including 3+ years delivering AI/ML-powered products from concept through GA.
• Proven record shipping at least 2 AI/ML products used by enterprise customers with measurable financial outcomes (e.g., margin improvement, cost reduction, or productivity gains).
• Hands-on data proficiency, including the ability to query or analyze large datasets (e.g., SQL or equivalent) and evaluate data quality, model performance, and signal reliability.
• Experience leading cross-functional execution with engineering, data science, design, sales, and marketing to launch and scale products.
• Demonstrated ability to build ROI and unit economics models and present business cases to executive audiences.
• Experience navigating complex enterprise sales cycles, including security, IT, and legal/procurement processes.
• Exceptional written and verbal communication skills; able to translate technical concepts for commercial audiences and commercial concepts for technical audiences.
• Bachelor’s degree in a technical, quantitative, or business field (e.g., Computer Science, Engineering, Mathematics, Economics) or equivalent practical experience.

Nice-to-Haves

• Experience in grocery, retail, or supply chain with familiarity in store operations, inventory management, and key margin levers.
• Exposure to agentic AI systems, LLM-based workflows, autonomous decision pipelines, prompt engineering, and AI evaluation/guardrail practices.
• Background with demand forecasting, replenishment, or inventory optimization products and metrics (e.g., OSA, service level, shrink).
• Familiarity with the retail tech stack, including WMS, POS, ERP/replenishment modules, EDI, and API-based integrations.
• Experience displacing incumbents or winning competitive takeouts in enterprise accounts.
• Early-career experience in management consulting, solutions architecture, or business analytics; comfortable running diagnostics and leading with financial outcomes.