Data & AI V&V Leader

Company: Alstom

Location: Bangalore

Lead the Data AI Verification Validation (VV) 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 VV Leader is accountable for defining and deploying the VV 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 VV 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 VV maturity and continues through the execution of a transformation roadmap including best practice deployment, organizational evolution, and staffing plan execution.

Organization: Digital Services / Data AI Governance

Reports to: Data AI Performance Director

Direct Reports:

• Data AI VV Engineers
• Data AI VV Architects

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

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

• Define and standardize verification and validation methodologies across the Data AI technology landscape.
• Promote and deploy automated testing.
• Promote and deploy CI/CD quality gates.
• Promote and deploy unit, integration, and end-to-end testing.
• Promote and deploy regression testing.
• Promote and deploy performance testing.

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

• Establish Data AI VV 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.

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

Mandatory

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

Preferred

• Cloud, Kubernetes, DevOps, or MLOps certifications.

• 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 VV 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.

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

• 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

Job Type: Experienced