Senior Hybrid Cloud Architect - (Data Center)

We seek a highly motivated, technology-focused individual passionate about improving and simplifying Ford’s highly complex global infrastructure environment across Cloud Platform, on-premises data centers, and distributed locations in all major regions. This role demands a proven people leader who will directly manage, mentor, and elevate a high-performing team of Domain and Solution Architects. You will be responsible for fostering a culture of engineering excellence, establishing architectural governance, and driving the strategic vision of your team. As a recognized thought leader, you will codify your team’s innovations by publishing reusable architectural patterns and authoring authoritative white papers that influence both internal enterprise strategy and the broader technology community.

The ideal candidate is a rare hybrid: a strategic people leader capable of defining multi-year technology roadmaps, a thought leader who shapes enterprise standards, and an elite engineer who can still roll up their sleeves to write advanced Infrastructure-as-Code (IaC) and build robust CI/CD pipelines to automate infrastructure deployment. You possess a profound, expert-level understanding of traditional datacenter operations, heterogeneous OS management (Windows and Linux), and hypervisor ecosystems. You are also tasked with looking toward the future, guiding our cloud migration strategies and laying the infrastructural groundwork for Next-Generation AI and MLOps workloads. If you are a proactive problem-solver who requires minimal direction and is passionate about driving infrastructural convergence while leading top-tier talent, we want you on our team.

People Management, Thought Leadership & Executive Communication

• Team Leadership & People Management: Directly manage, mentor, and inspire a specialized team of Infrastructure, Cloud, and Solution Architects. Handle talent acquisition, career development, performance management, and resource allocation to build a high-performing, autonomous architecture practice.
• Pattern Publishing & Architectural Governance: Establish and lead an Architecture Center of Excellence (CoE). Codify complex solutions by designing, documenting, and publishing reusable architectural patterns, reference architectures, and deployment blueprints to accelerate enterprise-wide adoption and ensure consistency.
• Thought Leadership & White Papers: Act as the vanguard of technological innovation by researching emerging tech and authoring comprehensive white papers, strategy documents, and internal engineering blogs. Document paradigm-shifting strategies (e.g., VMware-to-OpenShift Virtualization migrations, AI Infrastructure readiness) to guide the broader enterprise and establish industry presence.
• Executive Storytelling & Autonomous Consulting: Translate highly technical engineering concepts into compelling business strategies. Consult proactively with application, database, and security teams on cloud-native best practices and workload placement without waiting for top-down direction. Deliver architectural decision records (ADRs) to C-suite executives and review boards.

Datacenter, Virtualization & Hybrid Cloud Architecture

• Advanced Datacenter Engineering & Hardware Lifecycle: Lead holistic datacenter strategy, encompassing rack-and-stack operations, capacity planning, power/cooling considerations, high-performance storage arrays (SAN/NAS/NVMe), and complex compute topologies (Blade architectures, HCI).
• Enterprise Virtualization Transformation: Manage massive-scale legacy hypervisor environments (VMware vSphere, ESXi, vCenter). Architect and lead the strategic migration pathway from traditional VMware infrastructures to modern, Kubernetes-native OpenShift Virtualization (KubeVirt), consolidating VM and container control planes.
• Mainframe Modernization & Integration: Design low-latency, high-throughput integration patterns between modern microservices and legacy Mainframe systems (e.g., IBM z/OS, DB2, CICS). Architect secure API enablement layers and event-driven architectures to unlock Mainframe data.
• Cloud Architecture & Infrastructure Strategy: Architect resilient, highly scalable hybrid cloud ecosystems bridging on-premises datacenters, GCP, and other public clouds, ensuring optimal workload placement based on cost, compliance, and performance.

Hands-on Engineering, OS Administration & Automation

• Advanced Infrastructure as Code (IaC) & Scripting: Maintain a hands-on technical edge by building and testing sophisticated automation frameworks to provision infrastructure. Utilize expert-level Terraform, Ansible (Playbooks, Automation Controller), PowerShell (for Windows automation), Python, and advanced Bash.
• CI/CD Pipelines for IaC: Architect, build, and maintain robust Continuous Integration and Continuous Deployment (CI/CD) pipelines specifically for infrastructure lifecycle management. Integrate automated testing, security scanning (e.g., tfsec, Checkov), and policy-as-code validations into infrastructure pipelines using tools like Jenkins, GitLab CI/CD, GitHub Actions, or Tekton to ensure safe, repeatable deployments.
• Heterogeneous OS Administration (Windows & Linux): Act as the highest escalation point for both Windows and Linux ecosystems. Manage deep Windows Server administration, Active Directory (AD) topologies, Group Policy Objects (GPOs), and WSUS/SCCM frameworks alongside advanced Linux (RHEL/RHCOS) kernel tuning and troubleshooting.
• GitOps & Application Delivery: Architect and implement declarative, GitOps-driven application and infrastructure deployment methodologies utilizing tools such as ArgoCD, Flux, Helm, and Kustomize. Establish immutable infrastructure paradigms to prevent configuration drift.

Future-State Enablement: Cloud Migrations & AI Infrastructure

• Large-Scale Cloud Migration Execution: Architect and govern complex "lift-and-shift" and "refactor-to-cloud" migration programs from legacy datacenters to public cloud providers (GCP, AWS, Azure) utilizing enterprise migration frameworks and methodologies.
• AI/MLOps Infrastructure Readiness: Design scalable infrastructure to support Artificial Intelligence and Machine Learning workloads. Provision and manage GPU-accelerated node pools (NVIDIA vGPUs), high-throughput AI storage, and integrated MLOps platforms (e.g., OpenShift AI, Kubeflow) to support data science teams.

Mandatory Skillsets

1. Datacenter Operations & Architecture: Expert-level experience designing, building, and operating large-scale on-premises datacenters, including deep knowledge of server hardware lifecycle, complex storage fabrics, and bare-metal provisioning.
    
2. Enterprise Virtualization (VMware / OpenShift): Deep, hands-on expertise managing extensive hypervisor environments. Must have strong experience with either VMware (vSphere, vCenter, vSAN, NSX) OR OpenShift Virtualization (KubeVirt), with the ability to lead transitions between the two.
    
3. IaC & CI/CD Pipeline Automation: Hands-on ability to write, review, and deploy infrastructure scripts using Terraform, Ansible, Python, PowerShell, or Bash, and proven experience building automated CI/CD pipelines (e.g., GitLab CI, GitHub Actions, Jenkins) to test, secure, and deploy that IaC code at scale.
    
4. Heterogeneous OS & Systems Management: Extensive administrative experience across both Windows ecosystems (Windows Server, Active Directory, PowerShell automation) and Linux environments (RHEL, systemd, kernel tuning).
    
5. Containerization & Kubernetes: Deep architectural understanding of Red Hat OpenShift Container Platform (4.x) and core Kubernetes primitives at an enterprise scale.
    
6. People Leadership & Mentorship: Proven track record of managing, leading, and mentoring teams of Architects or Senior Engineers in an enterprise setting.
    
7. Mainframe Familiarity: Strong conceptual and integration experience with legacy Mainframe environments, specifically understanding how to bridge traditional z/OS architectures with modern cloud-native systems.

Good-to-Have (Preferred) Skillsets

1. Cloud Migration Experience (GCP / AWS / Azure): Demonstrated success in leading large-scale enterprise migrations from on-premises datacenters to hyper-scale public clouds using native migration tools and methodologies. GCP experience is highly preferred.
2. AI Infrastructure & MLOps: Experience architecting infrastructure specifically for AI/ML workloads. Familiarity with GPU orchestration on Kubernetes, MLOps tooling (Kubeflow, MLflow, OpenShift AI), and managing large data streams for model training and inference.
3. Advanced Networking & Security: Experience with Software-Defined Networking (SDN), hybrid cloud connectivity (GCP Cloud Interconnect, Direct Connect), and implementing Zero-Trust network security architectures.

You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!

As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder…or all of the above? No matter what you choose, we offer a work life that works for you, including:
• 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.

This position is leadership level 6 and ranges from $115,500-$218,100.
 

Final determination of 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.

For more information on salary and benefits, click here: https://fordcareers.co/LL6

Visa sponsorship is not available for this position.

Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.

This position is hybrid with a requirement to be onsite four or more days per week. 

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