Data & AI V&V Leader

Purpose of the Job

Lead the Data & AI Verification & Validation (V&V) function to ensure all Data & AI solutions delivered by the organization are reliable, secure, scalable, and compliant with Alstom engineering and quality standards.

The Data & AI V&V Leader is accountable for defining and deploying the V&V strategy, governance, methodologies, tools, and organization across the complete Data & AI governance scope.

The role works closely with Agile squads to embed quality engineering practices throughout the software development lifecycle, promoting a "quality built-in" culture rather than end-of-cycle validation.

As the Software Quality Engineering leader within the Data & AI Governance organization, the Data & AI V&V Leader ensures every Agile squad delivers production-ready, secure, and reliable solutions while continuously improving engineering excellence.

The mission starts with a comprehensive assessment of the current V&V maturity and continues through the execution of a transformation roadmap including best practice deployment, organizational evolution, and staffing plan execution. 

Organization

Organization: Digital Services / Data & AI Governance

Reports to: Data & AI Performance Director

Direct Reports:

• Data & AI V&V Engineers
• Data & AI V&V Architects

Key Stakeholders

Internal

• Product Owners / Program Managers
• Data Engineers
• ML Engineers
• Data Scientists
• Data & Software Architects
• Heads of Data & AI Delivery Teams

External

• Technology Partners
• Software Vendors
• Engineering Partners

Main Responsibilities

Define the Data & AI V&V Strategy

• Perform a comprehensive audit of the current V&V organization, processes, tools, and maturity.
• Identify risks, technical debt, and improvement opportunities.
• Define and execute the Data & AI V&V transformation roadmap.
• Establish quality KPIs and reporting.

Deploy Software Quality Engineering Best Practices

• Define and standardize verification and validation methodologies across the Data & AI technology landscape.
• Promote and deploy:
  • Automated testing
  • CI/CD quality gates
  • Unit, integration, and end-to-end testing
  • Regression testing
  • Performance testing

Organization & People Management

• Build and develop the Data & AI V&V organization.
• Build and execute the staffing plan.
• Recruit, onboard, and develop V&V engineers.
• Provide hierarchical management, coaching, and career development.
• Foster a strong software engineering and quality culture.

Governance

• Establish Data & AI V&V governance across all Data & AI products.
• Define mandatory software quality gates before production deployment.
• Ensure compliance with Alstom engineering standards.
• Support executive reviews through quality reporting and risk assessment.

Agile Quality Leadership

• Define and promote V&V practices adapted to Agile delivery.
• Embed V&V engineers within Agile squads.
• Ensure verification and validation activities are integrated into sprint planning, refinement, development, and release cycles.

Required Qualifications

Education

Mandatory

• Master's degree in Computer Science, Software Engineering, Data Engineering, or equivalent.

Preferred

• Cloud, Kubernetes, DevOps, or MLOps certifications. 

Experience

Mandatory

• 10+ years of experience in Software Engineering, Data Engineering, AI Engineering, or Quality Engineering.
• Significant experience managing engineering teams.
• Proven experience defining and deploying enterprise-scale V&V strategies.
• Experience leading organizational transformation.
• Experience with modern Data & AI platforms and cloud-native technologies.
• Proven experience working within Agile software delivery organizations.
• Experience collaborating with cross-functional Agile squads.
• Experience implementing Software Quality Engineering practices in Agile and DevOps environments.

Preferred

• Experience in railway, industrial, or safety-critical environments. 

Competencies & Skills

• Strong leadership and people management
• Technical credibility
• Software Quality Engineering
• Test Automation
• AI/ML Solution Validation
• Python
• Containerization
• CI/CD
• DevOps
• Risk Management
• Excellent communication and stakeholder management
• Continuous improvement mindset
• Strong execution and delivery focus
• Agile methodologies