Data & AI V&V Leader
Role Overview
Lead the Data & AI Verification & Validation function to ensure solutions are reliable, secure, scalable, and compliant with engineering and quality standards.
Define and deploy V&V strategy, governance, methods, tools, and organizational capability across Data & AI.
The role is within Digital Services / Data & AI Governance and reports to the Data & AI Performance Director.
Direct reports include Data & AI V&V Engineers and Architects.
Key Skills for This Role
Full Job Posting
Role purpose
Lead the Data & AI Verification & Validation function to ensure solutions are reliable, secure, scalable, and compliant with engineering and quality standards.
Define and deploy V&V strategy, governance, methods, tools, and organizational capability across Data & AI.
The role is within Digital Services / Data & AI Governance and reports to the Data & AI Performance Director.
Direct reports include Data & AI V&V Engineers and Architects.
Strategy and quality engineering
- Assess current V&V organization, processes, tools, and maturity; identify risks, technical debt, and improvements.
- Define and execute a transformation roadmap and establish quality KPIs and reporting.
- Standardize V&V methods and deploy automated testing, CI/CD quality gates, unit, integration, end-to-end, regression, and performance testing.
Organization and governance
- Build the V&V organization and staffing plan; recruit, onboard, coach, and develop V&V engineers.
- Establish governance across Data & AI products, mandatory quality gates before production, and compliance with Alstom engineering standards.
- Support executive reviews with quality reporting and risk assessment.
Agile quality leadership
- Embed V&V engineers in Agile squads and integrate validation into sprint planning, refinement, development, and releases.
- Promote quality engineering throughout the software development lifecycle and foster a strong engineering culture.
Mandatory qualifications
- Master’s degree in Computer Science, Software Engineering, Data Engineering, or equivalent.
- 10+ years in Software Engineering, Data Engineering, AI Engineering, or Quality Engineering.
- Significant engineering-team management experience and proven enterprise-scale V&V strategy and transformation experience.
- Experience with modern Data & AI platforms, cloud-native technologies, Agile delivery, cross-functional squads, and Software Quality Engineering in Agile and DevOps.
Preferred qualifications
- Cloud, Kubernetes, DevOps, or MLOps certifications are preferred.
- Experience in railway, industrial, or safety-critical environments is preferred.
Listed competencies
- The posting lists leadership and people management, technical credibility, Software Quality Engineering, test automation, AI/ML solution validation, Python, containerization, CI/CD, DevOps, and risk management.
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