Director, Test Architecture

Director, Test Architecture

is a senior individual contributor leadership role responsible for defining the future technical direction of Verification & Validation test architecture. This role will serve as the principal technical authority for AI‑Assisted and AI‑Led testing innovation, test framework architecture, and next‑generation V&V operating models across on‑board and off‑board software products.

Working through technical influence rather than direct people management, this person will architect scalable test frameworks, reusable automation assets, AI‑assisted test design patterns, intelligent regression strategies, and closed‑loop analytics that transform V&V from a reactive execution function into a predictive, automation‑first, data‑driven, software first engineering capability.

The ideal candidate is self‑driven, deeply technical, and future‑facing—able to look beyond immediate process gaps and define how Ford should model, optimize, and scale testing operations around AI. This includes leading AI‑Assisted value stream mapping for human‑in‑the‑loop analysis and AI‑Led operating‑model design for autonomous optimization, identifying high‑value intervention points across the V&V lifecycle, and translating emerging AI/ML capabilities into practical architecture, standards, governance, and measurable quality outcomes.

This role will partner across V&V, software engineering, systems engineering, DevSecOps, data analytics, simulation, lab infrastructure, and product teams to establish a common AI‑Led test architecture that improves coverage, cycle time, defect detection effectiveness, traceability, reuse, and release confidence.

Key Responsibilities

• AI Test Architecture Leadership: Define and own the reference architecture for AI‑Assisted and AI‑Led V&V test frameworks, including reusable patterns, common libraries, data interfaces, orchestration models, reporting integration, and governance standards.
• Future‑State V&V Operating Model: Shape how Ford models testing operations around AI, moving beyond tactical automation fixes to a predictive, closed‑loop, intelligence‑driven V&V capability.
• AI‑Assisted Value Stream Mapping and AI‑Led Optimization: Lead technical value stream mapping across requirements, test design, test planning, execution, defect triage, analytics, and release readiness to identify where AI‑Assisted workflows can augment engineering decisions and AI‑Led capabilities can automate repeatable, data‑driven interventions to reduce waste, improve flow, and increase engineering leverage.
• Test Framework Modernization: Architect scalable frameworks for test automation, AI‑assisted Gherkin authoring, automated test code generation, smart regression selection, failure pattern detection, coverage heat maps, and reusable test assets.
• Technical Strategy & Roadmap: Develop multi‑year technical roadmaps for AI‑Assisted and AI‑Led V&V innovation, including pilots, reference implementations, adoption milestones, KPI targets, and convergence plans across teams and toolchains.
• Cross‑Functional Technical Influence: Lead through influence across V&V, software engineering, systems engineering, DevSecOps, simulation, lab infrastructure, analytics, and product teams to drive adoption of common technical standards without relying on direct reporting authority.
• Data, Analytics & Closed‑Loop Intelligence: Define how test data, defect data, requirements traceability, execution evidence, and release metrics should be structured and connected to enable AI‑Assisted insights, AI‑Led closed‑loop recommendations, and measurable improvements in quality outcomes.
• Governance, Standards & Reuse: Establish technical standards for framework design, repository structure, data quality, model usage, evidence capture, traceability, configuration management, security, and responsible AI practices within V&V.
• Innovation Incubation: Identify, prototype, and scale high‑impact AI‑Assisted and AI‑Led use cases such as autonomous test exploration, requirements‑to‑test generation, anomaly detection, root‑cause assistance, test optimization, and predictive release readiness.
• Executive Technical Communication: Translate complex AI, data, and test architecture concepts into clear technical recommendations, business cases, implementation plans, and leadership‑ready narratives tied to quality, speed, cost, and risk reduction.

Must‑Have Qualifications

• Senior Leadership Experience: Proven experience at a Director or senior leadership level within software, software architecture, test management, systems integration, software quality, or automotive product development.
• Global Team Leadership: Demonstrated ability to lead, mentor, and inspire global teams of managers and technical leaders, establish operating models, and drive execution across complex vehicle programs and software release plans.
• Modern Tool Proficiency: Experience with enterprise lifecycle and test management tools such as Jira, Test Case Management, Program Management, dashboards, KPI reporting, and end‑to‑end traceability methodologies.
• Executive Communication: Exceptional communication and presentation skills, with a track record of articulating complex technical risks, bottlenecks, status, and recommendations clearly to senior executives and external partners.

What You’ll Bring (Qualifications)

• V&V Expertise: Strong, deep knowledge of test planning, test execution governance, defect management, risk mitigation, software release readiness, milestone reviews, and quality escalation processes.
• Advanced Testing Innovation: Experience integrating test automation, AI‑enabled testing methodologies, process optimization, and advanced data analytics into test management practices.
• Advanced Testing Innovation: Experience integrating test automation, AI‑Assisted testing methodologies, AI‑Led optimization patterns, process optimization, and advanced data analytics into test management practices.

Nice‑to‑Have Qualifications

• V&V Expertise: Strong, deep knowledge of test planning, test execution governance, defect management, risk mitigation, software release readiness, milestone reviews, and quality escalation processes.
• Advanced Testing Innovation: Experience integrating test automation, AI‑enabled testing methodologies, process optimization, and advanced data analytics into test management practices.
• Advanced Testing Innovation: Experience integrating test automation, AI‑Assisted testing methodologies, AI‑Led optimization patterns, process optimization, and advanced data analytics into test management practices.

Role Evaluation Criteria

• Communication: Requires executive‑level communication skills to present highly technical data, execution bottlenecks, risk assessments, and readiness status as clear, actionable strategic updates to senior leadership, chief reviewers, and cross‑functional forums.
• Discretion / Latitude: Exercises high latitude and decision‑making authority over the global software test management strategy, setting validation baselines, gating software releases, and determining the deployment of department budgets and supplier resources.
• Influence: Exerts broad influence across VV organizations, software development teams, program steering committees, and quality forums to ensure digital integrity standards and robust validation protocols are prioritized.
• Impact: Directly impacts the quality, reliability, and security of Ford's on‑board and off‑board digital products, preventing software escapes and ensuring seamless vehicle launches.
• Problem Solving: Solves highly complex, multi‑variable engineering challenges related to defect tracking, resource constraints, system bottlenecks, and software integration issues across global programs.
• Scope: Global oversight covering test planning and management across all designated vehicle platforms, on‑board/off‑board software products, and global program execution.
• Strategy: Drives the long‑term roadmap for V&V tool modernization, and engineering toolchain integration (e.g., Jira, Test Case Management, automated KPI reporting).
• Technical Expertise: Combines deep technical proficiency in modern software development methodologies (Agile, SAFe) and toolchain environments.