Cloud-Native Security & AI Architect (GCP / Zero Trust)

Ford Credit is seeking a Cloud-Native Security & AI Architect to guide on-prem workload migrations into a secure, well-architected GCP environment, while shaping their approach to safe and effective AI enablement.

About the Role: Ford Credit is accelerating its transition to a Zero-Trust security model on Google Cloud Platform (GCP) and maturing their enterprise cloud security patterns. This role will help establish practical reference architectures, answering various “How do I do X securely?” questions from internal teams, driving clarity where standards are still emerging.

What Success Looks Like (6–12 Months):

• Documented, adopted reference architectures and patterns for Zero Trust on GCP.
• Reduced critical security gaps across migrated workloads; measurable maturity lift.
• Repeatable Apigee patterns established; known gaps documented with remediation backlog and owners.
• Teams self-serve with “How to do X securely?” guides; faster decision cycles and fewer escalations.
• Safe, pragmatic AI enablement patterns integrated into SDLC with clear guardrails and logging.
• Established security governance frameworks and stage-gates with both automation and human-in-the-loop processes.

Responsibilities:

Zero-Trust Cloud Security Architecture (GCP) – primary focus

• Define and mature security architecture patterns and reference architectures for cloud-native workloads on GCP.
• Provide day-to-day guidance to application teams migrating from legacy environments to a new Zero-Trust GCP segment.
• Conduct gap analyses and recommend remediations to raise security maturity.
• Translate Ford’s Information Security Policies into actionable architecture guidance and guardrails.
• Establish “golden paths” for securing RPC endpoints, service-to-service auth, workload identity, runtime security, and logging.
• Design and document secure patterns for hybrid connectivity, ensuring safe data exchange and identity federation between on-premise data centers and GCP.
• Develop a holistic security strategy for critical third-party SaaS applications, focusing on identity integration, data governance, and unified visibility.
• Partner with threat modeling, networking, and data architecture teams to ensure holistic, risk-balanced designs.

API & Apigee Security Enablement

• Define patterns for securing APIs and RPC endpoints with Apigee.
• Identify platform gaps; collaborate with Ford’s Apigee owner to drive improvements and reusable examples.

AI Architecture (Agentic SDLC) – secondary focus

• Evaluate AI-enabled solutions for safety and security.
• Define secure agent patterns for SDLC use cases.
• Apply AI safety best practices.
• Design human-in-the-loop, decision traceability, and auditable logging for AI-assisted decision flows.

Process & Enablement

• Create and maintain clear, consumable architecture documentation and standards.
• Mentor teams; answer questions rapidly; help the org balance speed with security in a zero-trust context.
• Contribute to a pragmatic roadmap to improve security maturity across the portfolio.

Qualifications:

Minimum Qualifications

• 10+ years of IT experience with 7+ years in cloud architecture/engineering with 4+ years focused on cloud security.
• Deep hands-on experience with GCP services relevant to security.
• Proven experience designing or maturing Zero-Trust architectures.
• Strong understanding of OAuth/OIDC, service-to-service auth, token flows, and API security patterns.
• Experience designing security for hybrid architectures that connect modern cloud platforms with traditional enterprise data centers.
• Experience with SaaS security frameworks and tools.
• Integrate security seamlessly into the CI/CD pipeline.
• Experience producing reference architectures, standards, and “golden paths” for engineering teams.
• Good knowledge of security.
• Hands-on use of AI tools to improve productivity.
• Excellent communication and stakeholder enablement skills.

Preferred Qualifications

• GCP security certifications.
• Experience with Apigee at enterprise scale.
• Familiarity with LLM/agent attack vectors and mitigations.
• Exposure to spec-driven development and content-distributed architectures.
• Comfortable navigating ambiguity and building standards in-flight during large-scale migrations.