Data & AI V&V Leader

Alstom Transportation; Bengaluru; On-site; INR 5,000,000 - 9,000,000; Full time

Job summary

Alstom Transportation is seeking a Data AI VV Leader to define and deploy the VV strategy across the Data AI governance scope. You will ensure reliable, secure, scalable solutions and embed quality practices throughout the software development lifecycle.

You will lead a transformation roadmap, establish quality KPIs, and collaborate with Agile squads, engineers, and stakeholders to deliver production-ready solutions and governance across all Data AI products.

Qualifications

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

Responsibilities

• Define the Data AI VV Strategy and audit current VV org/processes/tools/maturity.
• Deploy verification and validation methodologies across Data AI tech landscape.
• Promote and deploy automated testing and CI/CD quality gates.
• Integrate VV engineers within Agile squads and sprint cycles.
• Build and develop the Data AI VV organization and staffing plan.

Skills

Leadership

People management

Software Quality Engineering

Test Automation

AI/ML Solution Validation

Python

Containerization

CI/CD

DevOps

Risk Management

Agile methodologies

Cloud

Kubernetes

MLOps

Education

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

Tools

Cloud

Kubernetes

DevOps

MLOps

Job description

Job Summary

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

Organization: Digital Services / Data AI Governance

Reports to: Data AI Performance Director

Direct Reports:

• Data AI VV Engineers


• Data AI VV 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 VV Strategy

• 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.

Deploy Software Quality Engineering Best Practices

• 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.

Organization People Management

• 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.

Governance

• 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.

Agile Quality Leadership

• 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.

Required Qualifications

Education

Mandatory

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

Preferred

• Cloud, Kubernetes, DevOps, or MLOps certifications.

Experience

• 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.

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

Job Type: Experienced