Principal AI Architect

Ford • ,

14h • $132,800 - $250,800 • Remote

About The Position

Ford Credit is seeking a Principal AI Architect to shape its enterprise AI strategy and turn it into secure, cloud-native, production-ready systems. This leadership-level player-coach will manage and develop AI, cloud, and security architects while directly owning selected high-impact architecture work. The role will establish reusable standards and delivery practices for AI-native software development, governed agentic systems, and technology modernization.
The Principal AI Architect provides enterprise direction for how Ford Credit designs, delivers, secures, and operates AI-enabled technology. Working across business and technology teams, this leader defines target and transition architectures, evaluates investment and risk trade-offs, and translates strategic decisions into practical roadmaps, reference architectures, standards, and implementation commitments. The role requires both executive-level judgment and the ability to test architectural assumptions against working systems and operational evidence.
A central focus is building an AI-native software delivery lifecycle that connects business intent and clear specifications to bounded execution, trustworthy verification, operational evidence, and continuous improvement. The Principal AI Architect also guides the design of production agentic systems, including their models, enterprise context, retrieval, tools, memory, orchestration, permissions, evaluations, observability, and recovery mechanisms. Security, human oversight, and auditable controls must be built into these systems, with autonomy matched to the consequences of each action.
The role guides cloud-native architecture and the modernization of legacy, mainframe, on-premises, SaaS, and cloud systems so they can support AI-assisted and agentic change safely. By converting recurring challenges into reusable golden paths and platform capabilities, the Principal AI Architect helps teams make sound decisions without creating a central approval bottleneck. Success includes an adopted AI architecture roadmap, production-ready agentic patterns, measurable improvements in delivery and risk management, and an architecture team with clear ownership and growing independent capability.

Requirements

• A bachelor’s degree in computer science, engineering, information systems, cybersecurity, or a related field, or equivalent practical experience.
• At least 12 years of progressive technology experience, including at least eight years in architecture roles and sustained responsibility for enterprise or cross-domain decisions.
• Experience architecting and operating enterprise AI/ML systems in production, including generative AI, large language models, retrieval-augmented generation, agentic workflows, evaluation, observability, and model lifecycle management.
• Deep cloud architecture experience on Google Cloud or a comparable hyperscaler.
• Strong security architecture expertise spanning Zero Trust, identity, authorization, secrets, APIs, threat modeling, data protection, and software supply-chain security.
• A strong understanding of AI safety and security risks is essential.
• A record of creating standards, reference architectures, roadmaps, and guardrails used across teams.
• Fluency in modern software delivery and production operations.
• Formal people-management experience.
• The ability to communicate complex technical and investment trade-offs to both executives and engineers.

Nice To Haves

• A master’s degree in a related discipline.
• Relevant Google Cloud professional certifications.
• Hands-on familiarity with Google Cloud AI, data, compute, security, and integration services.
• Experience transforming enterprise delivery practices around specifications and automated evaluation.
• Modernizing complex hybrid estates.
• Working in financial services or another highly regulated environment.
• Taking proofs of concept through enterprise adoption.
• Strong systems thinking and an ability to convert local learning into reusable architecture and operating-model improvements.

Responsibilities

• Define Ford Credit’s multi-year enterprise AI architecture strategy, target states, transition roadmaps, standards, and investment priorities.
• Establish an AI-native software delivery lifecycle built around explicit specifications, bounded execution, automated validation, evidence, and learning loops.
• Create reusable patterns for architecture manifests, technical plans, contracts, acceptance criteria, authority boundaries, escalation rules, and evidence bundles.
• Architect production agentic systems that integrate models, retrieval, tools, skills, memory, state, orchestration, permissions, evaluation, observability, and recovery.
• Define risk-tiered autonomy, checkpoints, pause gates, human oversight, and auditable decision trails for consequential actions.
• Establish evaluation practices spanning automated and regression testing, adversarial testing, human review, user acceptance, and production outcome monitoring.
• Set patterns for authoritative enterprise knowledge, including provenance, freshness, retrieval, versioning, structured context, and durable memory.
• Design and govern scalable AI applications and platforms on Google Cloud, with appropriate use of services such as Vertex AI, Gemini, GKE, Cloud Run, BigQuery, and Pub/Sub.
• Embed Zero-Trust principles, identity and access controls, data protection, software supply-chain security, and incident response into AI and cloud architectures.
• Address AI-specific risks, including prompt injection, data leakage, tool misuse, excessive agency, insecure retrieval, poisoning, and unsafe generated code.
• Guide the modernization of hybrid and legacy systems through modular architectures, APIs, events, observability, and practical transition plans.
• Turn architectural decisions and lessons learned into reference architectures, golden paths, validators, templates, runbooks, and platform capabilities.
• Advise senior leaders and build alignment across engineering, product, cybersecurity, data, legal, privacy, risk, procurement, and operations.
• Manage and develop an assigned team of architects through clear priorities, delegation, coaching, performance management, and succession planning.
• Use enterprise-approved AI tools responsibly to support eligible architecture research, synthesis, prototyping, and drafting while preserving confidentiality and human accountability.

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal