Senior Director, AI Engineering

Senior Director, AI Engineering | Ashley Furniture | Remote (US) | Full-Time

Ashley is the largest furniture manufacturer and retailer in North America, and we're redefining how customers shop for furniture. We're building intelligent, conversational agents that go beyond answering questions—they initiate value-driven conversations, design rooms, and orchestrate complex purchase flows across a two-sided marketplace connecting customers with merchants and retailers.

We're looking for a Senior Director, AI Engineering to lead the development of agentic AI systems that power our next-generation commerce platform. This is a hands‑on technical leadership role—you'll architect systems, write code, and ship products while building a team of world‑class AI engineers and applied scientists. You'll own the ML models, agent orchestration, and AI systems that power conversational shopping experiences across mobile, web, and third‑party AI platforms.

Your work will directly impact how millions of customers discover, visualize, and purchase furniture—and how thousands of merchants and retailers grow their businesses through our platform.

• Lead the design, development, and deployment of production agentic AI systems that power conversational commerce experiences
• Build decision systems combining traditional ML with large language models (LLMs)—modeling short‑term context from active conversations and maintaining long‑term customer memory
• Develop multi‑agent architectures with specialized orchestration for shopping, sales enablement, and customer support use cases
• Design and implement RAG systems, tool use patterns, and memory architectures that enable personalized, context‑aware interactions
• Drive post‑training and fine‑tuning strategies to adapt foundation models for commerce‑specific tasks
• Build integrations with third‑party AI platforms—shipping features that put our products in front of customers wherever they're already using AI
• Establish evaluation frameworks, quality metrics, and measurement methodologies for agent performance at scale
• Partner with product, design, and experience teams to ship features that improve customer engagement, conversion, and satisfaction
• Build and grow a team of AI engineers and applied scientists—hire exceptional talent, set technical direction, and develop people

• Deep experience building customer‑facing AI products—you've shipped conversational AI, shopping assistants, or recommendation systems that real users interact with at scale
• Strong technical expertise with LLMs and agentic systems: RAG architectures, tool use, memory systems, multi‑agent coordination, prompt engineering, fine‑tuning, and evaluation frameworks
• Production ML experience—you understand the tradeoffs between model quality, latency, cost, and reliability. You've optimized inference, managed model serving infrastructure, and built observability into AI systems
• Hands‑on technical leader—you still close to the code, can debug production issues, and lead by example. You balance technical depth with people leadership
• Experience building and managing high‑performing teams—hiring, mentoring, and developing engineers. You've created environments where talented people do their best work
• Strong communication skills—you drive clarity across engineering, product, and business teams. You can translate technical complexity into business impact

• Experience in e‑commerce, retail, or marketplace environments
• Background in computer vision, multi‑modal AI, or 3D/spatial understanding
• Experience building integrations with AI platform providers (OpenAI, Anthropic, Google)
• Familiarity with MCP (Model Context Protocol) or similar standards for AI discoverability
• Experience with two‑sided marketplace dynamics—building for both consumer and merchant/retailer experiences

• Greenfield opportunity:
  Build agentic commerce from scratch s isn't incremental improvement—it's inventing a new category
• Build your team:
  Hire AI engineers and applied scientists, shape the technical bar, create the culture
• Unique domain:
  Furniture is ideal for agentic commerce—high‑consideration purchases, visual/spatial complexity, room design, styling. Problems that push the boundaries of what AI can do
• Two‑sided platform:
  Build AI that serves both consumers and the merchants/retailers who sell through us—compounding network effects
• Location:
  
  Remote (US‑based)
• Reports to:
  
  VP of AI, Customer, Retail & Sales
• Compensation:
  Competitive base + bonus + 3 weeks PTO

• Director

• Full-time

• Engineering and Information Technology
• Furniture and Home Furnishings Manufacturing