Director, AI Transformation Architect

About the role

The Director, AI Transformation Architect is a hands-on builder and transformation leader responsible for identifying, redesigning, and scaling how Ford’s Integrated Services organization ideates, assesses, plans, and executes its work by embedding AI into the highest-value workflows to improve speed, quality, decision-making, and customer impact across the team.

Responsibilities

• 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.
• 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.

Requirements

Strong technical fluency and a hand-on builder mindset, with 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, or agent-based systems that were adopted by real users, not just prototypes.

Strong product management fluency including discovery, customer research, PRDs, roadmaps, prioritization, launch readiness, stakeholder alignment, and product analytics.

Experience redesigning knowledge-work workflows or operating models at team or enterprise scale.

Ability to rapidly prototype, test with users, measure outcomes, and iterate.

Comfort working within enterprise constraints, including security, privacy, legal, IT, data access, and governance.

Ability to influence cross-functional teams and drive adoption without relying solely on formal authority.

Strong communication, documentation, training, storytelling, and collaboration skills, with the ability to bring skeptical teams along.

Qualifications

Experience in automotive, digital product, software, platform, or large-scale enterprise organizations.

Enterprise implementation experience, especially in environments with security, privacy, identity, legal, compliance, procurement, IT and data-access constraints.

Experience creating training, enablement, champion networks, and reusable playbooks for scaled adoption.

Background in workflow automation, developer tools, internal tooling, product operations, design operations, or AI enablement.

Experience building tools for teams rather than only consumer-facing applications.

Experience evaluating AI platforms, vendors, agent frameworks, and emerging enterprise AI tooling.

Understanding of AI safety, data governance, access control, auditability, and responsible AI practices.

Skills

Fluency in how modern AI-enablement workflows are built, deployed, governed, and scaled.

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.

Benefits

Immediate medical, dental, vision, and prescription drug coverage.

Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up childcare and more.

Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more.

Vehicle discount program for employees and family members and management leases.

Tuition assistance.

Established and active employee resource groups.

Paid time off for individual and team community service.

A generous schedule of paid holidays, including the week between Christmas and New Year’s Day.

Paid time off and the option to purchase additional vacation time.

Pay

Salary grade will be based on candidate's skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value.

Schedule

This position is hybrid (onsite four days per week) for candidates who are in commuting distance to a Ford hub location or remote for non-local candidates.