Director, AI Transformation Architect

Ford Ford · Auto · Dearborn, MI +1 · Ford Next Businesses

Director-level role focused on identifying, redesigning, and scaling AI-enabled workflows within Ford's Integrated Services organization. The role involves hands-on building and prototyping of AI agents, automation, and infrastructure to improve speed, quality, and decision-making across product management, engineering, and go-to-market functions. It emphasizes responsible AI implementation, governance, and driving adoption through training and best practices.

What you'd actually do

  1. Transform the Integrated Services Product Team Operating Model: Identify, redesign, and scale AI-enabled workflows across discovery, customer research, Product Requirement Document (PRD) roadmaps, prioritization, launch readiness, executive reviews, analytics, PMO, go-to-market, and post-launch learning.
  2. Build AI Agents, Automation and Infrastructure: Create, configure, test, and maintain AI agents, tools, workflows, and integrations using APIs, retrieval, orchestration, agent instructions, approved AI platforms, enterprise systems, and related technical patterns.
  3. Prototype, Pilot and Scale: Rapidly prototype with real users, validate workflow fit, identify failure modes, and move successful solutions from idea to prototype to pilot to scaled adoption, working through technical, operational, security, privacy, and change-management barriers.
  4. Create Reusable Capabilities and Playbooks: Build repeatable agents, templates, standards, workflows, and best practices for common product, PMO and GTM work, including customer insight synthesis and journey mapping, requirement generation, PRD review, competitive analysis, roadmap tradeoffs, launch planning and execution, risk reviews, business case development, and executive communication.
  5. Measure Impact: Define and track outcomes tied directly to business and customer value creation, including adoption, time saved, cycle-time reduction, decision speed, employee experience, quality improvements, rework reduction, revenue generation and business or customer outcomes from AI enabled workflows.

Skills

Required

  • AI agents
  • workflow orchestration
  • retrieval
  • APIs
  • human-in-the-loop flows
  • evaluations
  • agent instructions
  • building and prototyping
  • scaling AI adoption
  • governance
  • security
  • privacy

Nice to have

  • MCPs
  • CLIs
  • AGENT.md-style configurations

What the JD emphasized

  • hands-on builder
  • deeply technical
  • highly pragmatic
  • understand how AI agents work
  • configure and extend them
  • apply them in real-world enterprise contexts
  • build and prototype directly
  • scaled adoption
  • durable workflow change
  • measurable improvement
  • Strong technical fluency
  • hand-on builder mindset
  • familiarity across modern AI workflow patterns including APIs, retrieval, agent instructions, orchestration, evaluations, and human-in-the-loop flows
  • Experience building AI-enabled workflows, automations, internal tools

Other signals

  • AI agents
  • workflow orchestration
  • human-in-the-loop
  • enterprise AI
  • scaling AI adoption