Director, AI Transformation Architect

We are the movers of the world and makers of the future. We get up every day, roll up our sleeves, and build a better world - together. At Ford, we're all a part of something bigger than ourselves. Are you ready to change the way the world moves?

Integrated Services, including the Digital Product team at Ford, is undergoing an exciting evolution as we accelerate how we create, launch and go-to-market with leading digital experiences for customers inside and outside of the vehicle. Central to this acceleration is our ability to strategically and responsibly use AI, automation and intelligent workflows to fundamentally transform how we operate across Integrated Services organization and the Ford enterprise, including digital product management, vehicle development and planning, Project Management Office (PMO) and go-to-market.

In this position...

Reporting to the Global Head of Digital Product, Integrated Services, the AI Transformation Architect is a hands-on builder and transformation leader responsible for identifying, redesigning and scaling how Ford's Integrated Services organization ideates, assess, plans and executes our work by embedding AI into the highest-value workflows to improve speed, quality, decision-making, and customer impact across the team. This role sits at the intersection of product management, engineering, operations/PMO, vehicle development and cycle planning, and business teams, translating high-friction workflows into practical, AI-enabled systems that help us deliver better experiences faster and create leverage for the organization and our internal partners.

The ideal candidate is deeply technical, highly pragmatic - they must understand how AI agents work, how to configure and extend them, and how to apply them in real-world enterprise contexts. This role partners closely with Integrated Services leadership, as well as functional leaders across the enterprise (Security, Office of General Counsel, Privacy, Enterprise Technology, etc.) to ensure AI-enabled workflows are built responsibly, governed appropriately, and scaled with confidence. This person should be comfortable working with tools and patterns such as APIs, retrieval, workflow orchestration, evaluations, agent instructions, skill creation and human-in-the-loop flows. Familiarity with MCPs, CLIs, and AGENT.md-style configurations patterns is a plus, but the primary requirement is fluency in how modern AI-enablement workflows are built, deployed, governed and scaled. The ideal candidate will have a deep understanding of how teams work effectively in large, matrixed organizations across the hardware + software + customer experience loop, how to influence change in these organizations, and how to turn new capabilities into measurable business and customer impact.

This is a hands-on transformation role: the person will build and prototype directly, but success will be measured by scaled adoption, durable workflow change, and measurable improvement in how the Integrated Services organization operates.

Reporting to the Global Head of Digital Product, Integrated Services, the AI Transformation Architect is a hands-on builder and transformation leader responsible for identifying, redesigning and scaling how Ford's Integrated Services organization ideates, assess, plans and executes our work by embedding AI into the highest-value workflows to improve speed, quality, decision-making, and customer impact across the team.

What you'll do...

• 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.
• 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.
• 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.
• 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.
• 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.
• Drive Adoption and Behavior Change: Train teams, coach leaders, create champions, document best practices, and make AI-enabled workflows easy, safe and useful enough to become the default way of working.
• Establish Quality, Governance and Trust: Partner with security, legal, privacy, IT, PMO, go-to-market and engineering to ensure workflows are secure, compliant, auditable, explainable, and appropriate for enterprise use.
• Design Human-In-The-Loop Systems: Define where AI should act independently, where humans must review or approve, and how teams should manage risk, quality and accountability in AI-enabled workflows.
• Increase Leverage: Identify and automate repetitive, manual, duplicative, or low-value work so teams can spend more time on customer insight, product judgment, and execution.
• Evaluate Emerging AI Patterns: Stay current on AI agent frameworks, tooling, security models, governance practices, workflow automation approaches, and enterprise patterns, then translate the most practical opportunities into Ford use cases.

What you'll do...

• 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.
• 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.
• 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.
• 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.
• 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.
• Drive Adoption and Behavior Change: Train teams, coach leaders, create champions, document best practices, and make AI-enabled workflows easy, safe and useful enough to become the default way of working.
• Establish Quality, Governance and Trust: Partner with security, legal, privacy, IT, PMO, go-to-market and engineering to ensure workflows are secure, compliant, auditable, explainable, and appropriate for enterprise use.
• Design Human-In-The-Loop Systems: Define where AI should act independently, where humans must review or approve, and how teams should manage risk, quality and accountability in AI-enabled workflows.
• Increase Leverage: Identify and automate repetitive, manual, duplicative, or low-value work so teams can spend more time on customer insight, product judgment, and execution.
• Evaluate Emerging AI Patterns: Stay current on AI agent frameworks, tooling, security models, governance practices, workflow automation approaches, and enterprise patterns, then translate the most practical opportunities into Ford use cases.