Principal AI Architect

Ford Motor Company

. Define Ford Credit’s multi-year enterprise AI architecture strategy, target states, transition roadmaps, standards, and investment priorities .

Posted 10/6/2026full-timeRemote • North Carolina • United StatesLead💰 $132,800 - $250,800 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in defining and implementing enterprise AI architecture strategies, including risk management and evaluation practices. Proficient in cloud architecture on Google Cloud, with a strong focus on security and compliance in AI systems.

Highest-signal resume keywords

Enterprise AI Architecture StrategyGoogle Cloud ArchitectureZero Trust Security ArchitectureAI/ML Systems in ProductionPeople Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI-Native Software Delivery LifecycleGenerative AILarge Language ModelsModel Lifecycle ManagementAutomated TestingRisk-Tiered AutonomyArchitecting Production SystemsEvaluation and ObservabilityAPIs and Modular ArchitecturesData Protection

Soft Skills

Communication of Technical Trade-OffsCoaching and Performance Management

Tools & Technologies

Google CloudVertex AIGeminiGKECloud RunBigQueryPub/Sub

Certifications & Qualifications

Google Cloud Professional Certifications

Industry Keywords

AI Safety and Security RisksEnterprise Knowledge ManagementSoftware Supply-Chain SecurityCross-Domain DecisionsHuman Oversight

Tech Stack

Tools & technologies

BigQueryCloudCyber Security

About the role

Key responsibilities & impact

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 based on 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 integrating 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
Establish evaluation practices including 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 using services such as Vertex AI, Gemini, GKE, Cloud Run, BigQuery, and Pub/Sub
Embed Zero Trust, 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 modernization of hybrid and legacy systems through modular architectures, APIs, events, observability, and transition plans
Turn architectural decisions and lessons learned into reference architectures, golden paths, validators, templates, runbooks, and platform capabilities
Advise senior leaders and align engineering, product, cybersecurity, data, legal, privacy, risk, procurement, and operations teams
Manage and develop an assigned team of architects through prioritization, delegation, coaching, performance management, and succession planning
Use enterprise-approved AI tools for eligible architecture research, synthesis, prototyping, and drafting while preserving confidentiality and human accountability

Requirements

What you’ll need

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
At least eight years in architecture roles
Sustained responsibility for enterprise or cross-domain decisions
Experience architecting and operating enterprise AI/ML systems in production
Experience with 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
Strong understanding of AI safety and security risks
Record of creating standards, reference architectures, roadmaps, and guardrails used across teams
Fluency in modern software delivery and production operations
Formal people-management experience
Ability to communicate complex technical and investment trade-offs to executives and engineers
Legally authorized to work in the United States
Master’s degree in a related discipline, Google Cloud professional certifications, and hands-on familiarity with Google Cloud services are preferred

Benefits

Comp & perks

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
Family building benefits including adoption and surrogacy expense reimbursement
Fertility treatments
Vehicle discount program for employees and family members
Management leases
Tuition assistance
Established and active employee resource groups
Paid time off for individual and team community service
Generous schedule of paid holidays, including the week between Christmas and New Year’s Day
Paid time off
Option to purchase additional vacation time