Inventory Optimization & Planning Leader - AI-Driven

Ashley Furniture Industries, LLC; Tampa (FL); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health, Dental, Vision

Paid Vacation

Employee Discount

Professional Development

401(k) and Profit Sharing

Job summary

Ashley Furniture Industries Inc. is seeking a Manager, Inventory Optimization & Planning to own how inventory targets are set and calibrated across our distribution network, inbound pipeline, and retail footprint.

You will run target-setting logic, balance stock, and translate targets into actionable recommendations for field teams using AI-enabled tools. You will lead an agent-supported operating model, co-design planning tools, validate results, and communicate policy decisions to leadership.

Qualifications

• 5+ years of experience in inventory planning, supply chain analytics, or a closely adjacent quantitative operations role.
• Hands-on experience with inventory target setting and multi-node placement, including improving or rebuilding these approaches (not just operating someone else's settings).
• Experience building or co-building internal analytical tools, models, or recommendation engines adopted by real users.
• Strong SQL and Python skills for analysis, with the ability to write code directly when needed.
• Power BI (or equivalent) experience, including building useful semantic models and views—not just consuming dashboards.
• Experience leading projects and working groups across teams; direct people-leadership experience is a plus.
• Comfort working across systems of record, including an ERP-class execution system, a planning platform, and exception or action-message tooling.

Responsibilities

• Define the day-to-day decision logic behind inventory target setting, segmentation, service-level policy, and stock placement across the network—including set-level ratios and how a balanced position is defined.
• Shape how targets are set, not just what they are.
• Move the organization from periodic, manual recalibration to a near-continuous process supported by AI agents and a ranked recommendation queue, starting with repeatable monthly cycles for transfers and rebalancing.
• Stand up and tune AI agents that support the work: write the rules, validate outputs, and determine when an agent recommends versus when a human owns the decision.
• Partner directly with teams building recommendation engines and rebalancing tools; contribute to the logic, validate outputs, and ensure recommendations reflect what should be acted on.
• Support the evaluation and evolution of the planning stack; serve as a key voice in tooling decisions and help carry the path forward.
• Co-design next-gen recommendation tools alongside systems and intelligence partners—bringing the inventory and policy perspective while partnering with engineering teams to build durable solutions.
• Run rigorous validation cadences against new models, agents, and methods—including data tests with operating teams before scaling.
• Own the forecast-to-target handshake, ensuring forecasting signals route into the right inventory policy decisions and that the feedback loop runs both ways.
• Tell the story to leadership: why targets are set the way they are, what is drifting, what it is costing, and what actions are being taken.
• Develop analysts into agent operators and tool builders, not report builders; document the playbook so it can survive platform changes and team turnover.
• Own network-level supply chain performance: inventory health KPIs across site, regional, or network levels.

Skills

Inventory planning

SQL

Python

AI/agent tooling

Leadership

Tools

Power BI

ERP systems

Job description

Ashley Furniture Industries Inc. is seeking a Manager, Inventory Optimization & Planning to own how inventory targets are set and calibrated across our distribution network, inbound pipeline, and retail footprint.

You will run target-setting logic, balance stock, and translate targets into actionable recommendations for field teams using AI-enabled tools. You will lead an agent-supported operating model, co-design planning tools, validate results, and communicate policy decisions to leadership.