We are looking for a strategic and hands-on Product Manager to own the roadmap for our legacy supply chain products, drive their modernization, and lead the transformation strategy to make them AI-enabled and future-ready. This role sits at the intersection of legacy systems knowledge, digital transformation, and applied AI — ideal for someone who can balance stabilizing what exists today with building what comes next. You will work closely with engineering, design, customer success, and leadership to define a multi-year roadmap, prioritize modernization initiatives, and translate emerging AI capabilities into practical, revenue-generating or efficiency-driving features for supply chain customers. Key Responsibilities: Roadmap & Strategy Own and evolve the product roadmap for legacy supply chain products, balancing maintenance, modernization, and innovation. Define and communicate a clear transformation strategy — including migration paths, technical debt reduction, and phased modernization plans. Translate business goals into a prioritized backlog using data, customer feedback, and market/competitive analysis. Partner with leadership to align product strategy with company-wide digital transformation goals. Legacy Modernization Conduct in-depth audits of existing legacy products (architecture, UX, workflows, integrations) to identify modernization opportunities. Define migration strategies (re-platforming, re-architecting, incremental modernization) in collaboration with engineering. Manage the trade-offs between maintaining legacy stability and driving modernization velocity. Reduce technical debt while ensuring business continuity for existing customers. Supply Chain Domain Expertise Apply deep understanding of supply chain processes — procurement, inventory management, logistics, warehousing, demand planning, order fulfillment — to shape product decisions. Engage with customers and internal stakeholders to identify pain points in existing supply chain workflows. Benchmark against supply chain industry trends, standards, and competitor offerings. AI Strategy & Implementation Identify and prioritize opportunities to embed AI/ML capabilities into legacy products (e.g., demand forecasting, anomaly detection, intelligent automation, conversational interfaces, predictive analytics). Partner with data science/engineering teams to scope, build, and ship AI-powered features. Define success metrics for AI features and iterate based on performance and adoption data. Stay current on AI/LLM advancements and evaluate their applicability to supply chain use cases. Execution & Cross-Functional Leadership Write clear PRDs, user stories, and acceptance criteria for engineering teams. Work in agile/scrum environments — manage sprints, backlogs, and release planning. Collaborate with UX/design to ensure modernized products meet current usability standards. Act as the voice of the customer, gathering and synthesizing feedback from sales, support, and end users. Report roadmap progress, risks, and outcomes to executive stakeholders. Job Requirements: 5–8+ years of Product Management experience, with at least 2–3 years focused on legacy system modernization or platform transformation. Proven experience managing products in the supply chain / logistics / domain. Demonstrated experience defining and executing AI/ML-driven product features (not just familiarity — actual shipped implementation). Strong technical fluency — comfortable discussing architecture, APIs, data pipelines, and integration patterns with engineering teams. Experience managing trade-offs between legacy system constraints and modern technology adoption. Track record of building and communicating multi-quarter/multi-year roadmaps to executive stakeholders. Strong analytical skills — comfortable with data-driven decision-making and defining success metrics/KPIs. Excellent written and verbal communication skills; able to translate technical complexity into business language. Experience with specific supply chain platforms (e.g., SAP, Oracle SCM, Blue Yonder, Manhattan Associates, Kinaxis, or similar). Familiarity with AI/LLM implementation patterns (RAG, agentic workflows, forecasting models, recommendation systems). Experience leading re-platforming or cloud migration initiatives (on-prem to cloud, monolith to microservices). MBA or advanced degree in relevant field (not mandatory). Certification in Agile/Scrum (CSPO, PSPO) or Supply Chain (APICS/CSCP).