[Hiring] Director, Cloud & AI Infrastructure Operations @Ford Motor Company

Role Description

The Director, Cloud & AI Infrastructure Operations will be a senior technical leader responsible for the reliability, security, and cost-efficiency of Ford Credit's cloud and container-based application landscape, with a growing focus on AI infrastructure and secure AI enablement. This individual will operate at the intersection of cloud engineering, platform operations, cybersecurity, and emerging AI technologies — partnering closely with application teams, enterprise architecture, cloud platform teams, security engineering, and external technology partners.

Ford Credit's technology estate is increasingly hybrid — spanning Google Cloud Platform, containerized platforms (Kubernetes/OpenShift), traditional Ford data centers, and a rapidly growing footprint of AI-driven capabilities (LLMs, RAG pipelines, agentic automation). This Director will own the operational health, security posture, and cost efficiency of that hybrid estate, while also building Ford Credit's capability to safely and effectively adopt AI infrastructure and AI-assisted engineering tools. The role is both a hands-on technical leadership position and a strategic partner to the VP, translating emerging cloud/AI capabilities into governed, production-ready, cost-conscious solutions.

Responsibilities

What you'll do...

• Cloud & Container Operations
  • Provide operational leadership and support for applications running on Google Cloud Platform (GCP) and on container operating systems such as Kubernetes and/or OpenShift.
  • Maintain and evolve deep working knowledge of GCP services, GCP networking constructs, and secure architecture patterns; guide teams in designing and implementing secure solutions within GCP.
  • Lead the design and implementation of High Availability (HA) and Disaster Recovery (DR) infrastructure for applications spanning Google Cloud and Ford data centers, ensuring resiliency across hybrid environments.
• AI Infrastructure & Innovation
  • Build and apply familiarity with AI infrastructure concepts — including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), and Agentic AI solutions — to design and execute solutions that improve IT processes and drive automation.
  • Develop working knowledge of AI-powered IDEs (e.g., Cursor, Claude) and promote their effective, secure use within engineering teams to boost developer productivity.
  • Gain and apply working knowledge of Google AI services (e.g., Gemini Enterprise, AI Runtime, Vertex AI Search, Feature Store) to design and execute secure, production-grade AI solutions.
  • Partner with security engineering to identify, evaluate, and implement security controls and solutions that protect AI architectures and AI agents from emerging threats.
• Security & Compliance
  • Maintain working knowledge of application and infrastructure security scanning tooling — including SAST, SCA, IaC scanning, DAST, and API security testing — and ensure these are embedded into cloud and container delivery pipelines.
  • Ensure all cloud, container, and AI solutions adhere to Ford Credit and enterprise security, risk, and compliance standards.
• Cost & Value Management
  • Proactively identify and implement solutions to reduce infrastructure costs and AI token/consumption costs.
  • Develop and present metrics and dashboards to management demonstrating the operational, financial, and productivity benefits of implemented solutions.
• Collaboration & Leadership
  • Collaborate extensively across internal Ford Credit teams (application, infrastructure, security, architecture) as well as external partners, vendors, and Ford enterprise technology teams.
  • Mentor and develop technical talent within the team; act as a technical escalation point for complex cloud, container, and AI infrastructure issues.
  • Represent Ford Credit's cloud and AI infrastructure strategy in cross-functional and leadership forums.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field (or equivalent experience).
• Significant experience (typically 10+ years) in cloud infrastructure/platform engineering, with substantial hands-on experience on Google Cloud Platform.
• Proven experience operating and supporting applications on container platforms such as Kubernetes and/or OpenShift.
• Demonstrated experience designing and implementing secure cloud architectures, including GCP networking, IAM, and security controls.
• Experience designing and implementing HA/DR solutions across hybrid environments (cloud and on-premises data centers).
• Working knowledge of AI/ML infrastructure concepts (LLM, RAG, MCP, Agentic AI) and their practical application to IT operations and automation.
• Familiarity with AI-powered development tools (e.g., Cursor, Claude Code) and modern developer workflows.
• Working knowledge of Google AI/ML platform services (Gemini Enterprise, Vertex AI Search, Feature Store, AI Runtime, etc.).
• Understanding of security considerations unique to AI systems and AI agents (e.g., prompt injection, data leakage, model/agent access control).
• Working knowledge of security scanning tools/practices across SAST, SCA, IaC, DAST, and API security.
• Strong track record of cross-functional collaboration with internal and external stakeholders.
• Demonstrated ability to build business cases and present cost/benefit metrics to senior leadership.
• Strong leadership, communication, and people-management skills; experience leading technical teams.

Benefits

• Immediate medical, dental, vision and prescription drug coverage.
• Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care 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.